diff --git a/app.py b/app.py index ba1e857b438286dcc25522e3cfa34df8eaffeca4..27158502e9fa22ae0f6856298e4da1f936e8c014 100644 --- a/app.py +++ b/app.py @@ -27,7 +27,7 @@ To do that we added following text to the query: {} -All of the call were made from the same machine with the same internet connection with usage of the LiteLLM library which may adds some time overhead compared to pure curl calls. +All of the call were made from the same machine with the same internet connection with usage of the LiteLLM library which may adds some time overhead compared to pure curl calls. Call were made from Poland, UTC +1. Please take a look at the following project and let us know if you have any questions or suggestions. """ diff --git a/data/2024-01-17 12:38:58.304815_summary.csv b/data/2024-01-17 12:38:58.304815_summary.csv deleted file mode 100644 index 674459a1343a72c921d8c84956e53ecbf1d57e27..0000000000000000000000000000000000000000 --- a/data/2024-01-17 12:38:58.304815_summary.csv +++ /dev/null @@ -1,28 +0,0 @@ -model,language,template_name,execution_time,characters_count,words_count,chunk_sizes,chunk_generation_times,chunk_generation_times_by_chunk_sizes -Mistral-7B-Instruct-v0.2,english,call,,,,,, -Mistral-7B-Instruct-v0.2,english,json,3.6487972736358643,303.5,51.0,3.570588235294118,0.03324383567361271,0.001449326305389626 -Mistral-7B-Instruct-v0.2,english,markdown,4.151226162910461,358.0,60.0,3.58,0.03327744722366333,0.0006092002057602237 -Mistral-7B-Instruct-v0.2,japanese,call,,,,,, -Mistral-7B-Instruct-v0.2,japanese,json,0.9473649263381958,0.0,0.0,,, -Mistral-7B-Instruct-v0.2,japanese,markdown,0.8581207990646362,0.0,0.0,,, -Mixtral-8x7B-Instruct-v0.1,english,json,2.337923765182495,305.5,48.5,3.636904761904762,0.009715833834239416,0.00017000696402891426 -TinyLlama/TinyLlama-1.1B-Chat-v1.0,english,json,1.9294229745864868,334.0,55.5,3.5913978494623655,0.01203190895818895,0.0005004366755420837 -gemini-pro,english,json,,,,,, -gpt-3.5-turbo,english,call,2.724249005317688,303.0,52.5,,, -gpt-3.5-turbo,english,json,1.7111433148384094,282.25,48.5,4.342307692307692,0.017717334857353797,0.0006912943431051048 -gpt-3.5-turbo,english,markdown,2.6450350284576416,403.0,66.5,4.380434782608695,0.018466552962427555,0.0005482604451258303 -gpt-3.5-turbo,japanese,call,9.296517014503479,322.0,1.0,,, -gpt-3.5-turbo,japanese,json,5.7430419921875,229.5,4.0,1.1167883211678833,0.02545691406639823,0.0004982973938963198 -gpt-3.5-turbo,japanese,markdown,8.998926281929016,369.5,1.0,1.098068350668648,0.024078829327451527,0.0006811250911499464 -llama-2-70b-chat,english,call,,,,,, -llama-2-70b-chat,english,json,2.0344420671463013,292.0,43.5,3.4352941176470586,0.0120459423345678,0.0008612603182374274 -llama-2-70b-chat,english,markdown,3.0651516914367676,532.5,77.0,3.9444444444444446,0.013201815993697555,0.0003262027774235997 -llama-2-70b-chat,japanese,call,,,,,, -llama-2-70b-chat,japanese,json,5.301165580749512,459.0,49.0,1.9827213822894167,0.015144962471453211,0.00037437952061093125 -llama-2-70b-chat,japanese,markdown,10.500205397605896,2586.5,395.5,4.664562669071235,0.016482780386027827,0.00010443909883635945 -zephyr-7b-beta,english,call,,,,,, -zephyr-7b-beta,english,json,4.1515063643455505,357.5,60.0,3.8440860215053765,0.035762690087800385,0.0038104588643407896 -zephyr-7b-beta,english,markdown,4.133428335189819,348.0,62.0,3.625,0.0346326952179273,0.0010808045642794416 -zephyr-7b-beta,japanese,call,,,,,, -zephyr-7b-beta,japanese,json,1.044502854347229,0.0,0.0,,, -zephyr-7b-beta,japanese,markdown,0.8821841478347778,0.0,0.0,,, diff --git a/data/2024-01-17 12:39:37.086623_time_of_day_comparison.csv b/data/2024-01-17 12:39:37.086623_time_of_day_comparison.csv deleted file mode 100644 index 9ee6129232b30bd322cacec560ea5f763b1c39cd..0000000000000000000000000000000000000000 --- a/data/2024-01-17 12:39:37.086623_time_of_day_comparison.csv +++ /dev/null @@ -1,12 +0,0 @@ -model,time_of_day,execution_time,characters_count,words_count -Mistral-7B-Instruct-v0.2,morning,2.4013772904872894,165.375,27.75 -Mistral-7B-Instruct-v0.2,noon,,, -Mixtral-8x7B-Instruct-v0.1,noon,2.337923765182495,305.5,48.5 -TinyLlama/TinyLlama-1.1B-Chat-v1.0,noon,1.9294229745864868,334.0,55.5 -gemini-pro,noon,,, -gpt-3.5-turbo,morning,5.1754879752794904,316.3333333333333,28.25 -gpt-3.5-turbo,noon,5.12265948454539,338.6666666666667,32.666666666666664 -llama-2-70b-chat,morning,5.2554163336753845,967.5,141.25 -llama-2-70b-chat,noon,1.9137414693832397,292.0,43.5 -zephyr-7b-beta,morning,2.5529667139053345,176.375,30.5 -zephyr-7b-beta,noon,4.151261210441589,357.5,60.0 diff --git a/data/2024-01-18 10:30:01.312286_time_of_day_comparison.csv b/data/2024-01-18 10:30:01.312286_time_of_day_comparison.csv deleted file mode 100644 index c353b8fa2dfd2805072c64946b7686fc043f498c..0000000000000000000000000000000000000000 --- a/data/2024-01-18 10:30:01.312286_time_of_day_comparison.csv +++ /dev/null @@ -1,12 +0,0 @@ -model,time_of_day,execution_time,characters_count,words_count -Mistral-7B-Instruct-v0.2,morning,2.4013772904872894,165.375,27.75 -Mistral-7B-Instruct-v0.2,noon,2.43726247549057,165.375,27.75 -Mixtral-8x7B-Instruct-v0.1,noon,8.433558851480484,507.75,44.75 -TinyLlama/TinyLlama-1.1B-Chat-v1.0,noon,1.4488664865493774,162.0,27.625 -gemini-pro,noon,,, -gpt-3.5-turbo,morning,5.1754879752794904,316.3333333333333,28.25 -gpt-3.5-turbo,noon,5.076187094052632,323.5833333333333,26.083333333333332 -llama-2-70b-chat,morning,5.2554163336753845,967.5,141.25 -llama-2-70b-chat,noon,5.080266445875168,967.5,141.25 -zephyr-7b-beta,morning,2.5529667139053345,176.375,30.5 -zephyr-7b-beta,noon,2.5973838567733765,176.25,30.375 diff --git a/data/2024-01-22 12:13:19.498935_general_plot.csv b/data/2024-01-22 12:13:19.498935_general_plot.csv deleted file mode 100644 index dd6be7e77876d07df56c0943b6d72ac40de2172c..0000000000000000000000000000000000000000 --- a/data/2024-01-22 12:13:19.498935_general_plot.csv +++ /dev/null @@ -1,327 +0,0 @@ -path,plot_object,description -./html/plots/response_times.html,"Figure({ - 'data': [{'alignmentgroup': 'True', - 'hovertemplate': 'model=%{x}
execution_time=%{y}', - 'legendgroup': 'Mistral-7B-Instruct-v0.2', - 'marker': {'color': '#636efa', 'pattern': {'shape': ''}}, - 'name': 'Mistral-7B-Instruct-v0.2', - 'offsetgroup': 'Mistral-7B-Instruct-v0.2', - 'orientation': 'v', - 'showlegend': True, - 'textposition': 'auto', - 'type': 'bar', - 'x': array(['Mistral-7B-Instruct-v0.2'], dtype=object), - 'xaxis': 'x', - 'y': array([2.41931988]), - 'yaxis': 'y'}, - {'alignmentgroup': 'True', - 'hovertemplate': 'model=%{x}
execution_time=%{y}', - 'legendgroup': 'Mixtral-8x7B-Instruct-v0.1', - 'marker': {'color': '#EF553B', 'pattern': {'shape': ''}}, - 'name': 'Mixtral-8x7B-Instruct-v0.1', - 'offsetgroup': 'Mixtral-8x7B-Instruct-v0.1', - 'orientation': 'v', - 'showlegend': True, - 'textposition': 'auto', - 'type': 'bar', - 'x': array(['Mixtral-8x7B-Instruct-v0.1'], dtype=object), - 'xaxis': 'x', - 'y': array([8.43355885]), - 'yaxis': 'y'}, - {'alignmentgroup': 'True', - 'hovertemplate': 'model=%{x}
execution_time=%{y}', - 'legendgroup': 'TinyLlama/TinyLlama-1.1B-Chat-v1.0', - 'marker': {'color': '#00cc96', 'pattern': {'shape': ''}}, - 'name': 'TinyLlama/TinyLlama-1.1B-Chat-v1.0', - 'offsetgroup': 'TinyLlama/TinyLlama-1.1B-Chat-v1.0', - 'orientation': 'v', - 'showlegend': True, - 'textposition': 'auto', - 'type': 'bar', - 'x': array(['TinyLlama/TinyLlama-1.1B-Chat-v1.0'], dtype=object), - 'xaxis': 'x', - 'y': array([1.44886649]), - 'yaxis': 'y'}, - {'alignmentgroup': 'True', - 'hovertemplate': 'model=%{x}
execution_time=%{y}', - 'legendgroup': 'gemini-pro', - 'marker': {'color': '#ab63fa', 'pattern': {'shape': ''}}, - 'name': 'gemini-pro', - 'offsetgroup': 'gemini-pro', - 'orientation': 'v', - 'showlegend': True, - 'textposition': 'auto', - 'type': 'bar', - 'x': array(['gemini-pro'], dtype=object), - 'xaxis': 'x', - 'y': array([nan]), - 'yaxis': 'y'}, - {'alignmentgroup': 'True', - 'hovertemplate': 'model=%{x}
execution_time=%{y}', - 'legendgroup': 'gpt-3.5-turbo', - 'marker': {'color': '#FFA15A', 'pattern': {'shape': ''}}, - 'name': 'gpt-3.5-turbo', - 'offsetgroup': 'gpt-3.5-turbo', - 'orientation': 'v', - 'showlegend': True, - 'textposition': 'auto', - 'type': 'bar', - 'x': array(['gpt-3.5-turbo'], dtype=object), - 'xaxis': 'x', - 'y': array([5.12583753]), - 'yaxis': 'y'}, - {'alignmentgroup': 'True', - 'hovertemplate': 'model=%{x}
execution_time=%{y}', - 'legendgroup': 'llama-2-70b-chat', - 'marker': {'color': '#19d3f3', 'pattern': {'shape': ''}}, - 'name': 'llama-2-70b-chat', - 'offsetgroup': 'llama-2-70b-chat', - 'orientation': 'v', - 'showlegend': True, - 'textposition': 'auto', - 'type': 'bar', - 'x': array(['llama-2-70b-chat'], dtype=object), - 'xaxis': 'x', - 'y': array([5.16784139]), - 'yaxis': 'y'}, - {'alignmentgroup': 'True', - 'hovertemplate': 'model=%{x}
execution_time=%{y}', - 'legendgroup': 'zephyr-7b-beta', - 'marker': {'color': '#FF6692', 'pattern': {'shape': ''}}, - 'name': 'zephyr-7b-beta', - 'offsetgroup': 'zephyr-7b-beta', - 'orientation': 'v', - 'showlegend': True, - 'textposition': 'auto', - 'type': 'bar', - 'x': array(['zephyr-7b-beta'], dtype=object), - 'xaxis': 'x', - 'y': array([2.57517529]), - 'yaxis': 'y'}], - 'layout': {'barmode': 'relative', - 'legend': {'title': {'text': 'model'}, 'tracegroupgap': 0}, - 'margin': {'t': 60}, - 'template': '...', - 'xaxis': {'anchor': 'y', - 'categoryarray': [Mistral-7B-Instruct-v0.2, - Mixtral-8x7B-Instruct-v0.1, - TinyLlama/TinyLlama-1.1B-Chat-v1.0, - gemini-pro, gpt-3.5-turbo, - llama-2-70b-chat, zephyr-7b-beta], - 'categoryorder': 'array', - 'domain': [0.0, 1.0], - 'title': {'text': 'model'}}, - 'yaxis': {'anchor': 'x', 'domain': [0.0, 1.0], 'title': {'text': 'execution_time'}}} -})",Model endpoints response times -./html/plots/model_sizes.html,"Figure({ - 'data': [{'alignmentgroup': 'True', - 'hovertemplate': 'color=gpt-3.5-turbo
x=%{x}
y=%{y}', - 'legendgroup': 'gpt-3.5-turbo', - 'marker': {'color': '#636efa', 'pattern': {'shape': ''}}, - 'name': 'gpt-3.5-turbo', - 'offsetgroup': 'gpt-3.5-turbo', - 'orientation': 'v', - 'showlegend': True, - 'textposition': 'auto', - 'type': 'bar', - 'x': array(['gpt-3.5-turbo'], dtype=object), - 'xaxis': 'x', - 'y': array([0.]), - 'yaxis': 'y'}, - {'alignmentgroup': 'True', - 'hovertemplate': 'color=llama-2-70b-chat
x=%{x}
y=%{y}', - 'legendgroup': 'llama-2-70b-chat', - 'marker': {'color': '#EF553B', 'pattern': {'shape': ''}}, - 'name': 'llama-2-70b-chat', - 'offsetgroup': 'llama-2-70b-chat', - 'orientation': 'v', - 'showlegend': True, - 'textposition': 'auto', - 'type': 'bar', - 'x': array(['llama-2-70b-chat'], dtype=object), - 'xaxis': 'x', - 'y': array([0.]), - 'yaxis': 'y'}, - {'alignmentgroup': 'True', - 'hovertemplate': 'color=Mixtral-8x7B-Instruct-v0.1
x=%{x}
y=%{y}', - 'legendgroup': 'Mixtral-8x7B-Instruct-v0.1', - 'marker': {'color': '#00cc96', 'pattern': {'shape': ''}}, - 'name': 'Mixtral-8x7B-Instruct-v0.1', - 'offsetgroup': 'Mixtral-8x7B-Instruct-v0.1', - 'orientation': 'v', - 'showlegend': True, - 'textposition': 'auto', - 'type': 'bar', - 'x': array(['Mixtral-8x7B-Instruct-v0.1'], dtype=object), - 'xaxis': 'x', - 'y': array([56.]), - 'yaxis': 'y'}, - {'alignmentgroup': 'True', - 'hovertemplate': 'color=zephyr-7b-beta
x=%{x}
y=%{y}', - 'legendgroup': 'zephyr-7b-beta', - 'marker': {'color': '#ab63fa', 'pattern': {'shape': ''}}, - 'name': 'zephyr-7b-beta', - 'offsetgroup': 'zephyr-7b-beta', - 'orientation': 'v', - 'showlegend': True, - 'textposition': 'auto', - 'type': 'bar', - 'x': array(['zephyr-7b-beta'], dtype=object), - 'xaxis': 'x', - 'y': array([7.]), - 'yaxis': 'y'}, - {'alignmentgroup': 'True', - 'hovertemplate': 'color=Mistral-7B-Instruct-v0.2
x=%{x}
y=%{y}', - 'legendgroup': 'Mistral-7B-Instruct-v0.2', - 'marker': {'color': '#FFA15A', 'pattern': {'shape': ''}}, - 'name': 'Mistral-7B-Instruct-v0.2', - 'offsetgroup': 'Mistral-7B-Instruct-v0.2', - 'orientation': 'v', - 'showlegend': True, - 'textposition': 'auto', - 'type': 'bar', - 'x': array(['Mistral-7B-Instruct-v0.2'], dtype=object), - 'xaxis': 'x', - 'y': array([7.]), - 'yaxis': 'y'}, - {'alignmentgroup': 'True', - 'hovertemplate': 'color=TinyLlama/TinyLlama-1.1B-Chat-v1.0
x=%{x}
y=%{y}', - 'legendgroup': 'TinyLlama/TinyLlama-1.1B-Chat-v1.0', - 'marker': {'color': '#19d3f3', 'pattern': {'shape': ''}}, - 'name': 'TinyLlama/TinyLlama-1.1B-Chat-v1.0', - 'offsetgroup': 'TinyLlama/TinyLlama-1.1B-Chat-v1.0', - 'orientation': 'v', - 'showlegend': True, - 'textposition': 'auto', - 'type': 'bar', - 'x': array(['TinyLlama/TinyLlama-1.1B-Chat-v1.0'], dtype=object), - 'xaxis': 'x', - 'y': array([1.1]), - 'yaxis': 'y'}, - {'alignmentgroup': 'True', - 'hovertemplate': 'color=gemini-pro
x=%{x}
y=%{y}', - 'legendgroup': 'gemini-pro', - 'marker': {'color': '#FF6692', 'pattern': {'shape': ''}}, - 'name': 'gemini-pro', - 'offsetgroup': 'gemini-pro', - 'orientation': 'v', - 'showlegend': True, - 'textposition': 'auto', - 'type': 'bar', - 'x': array(['gemini-pro'], dtype=object), - 'xaxis': 'x', - 'y': array([0.]), - 'yaxis': 'y'}], - 'layout': {'barmode': 'relative', - 'legend': {'title': {'text': 'color'}, 'tracegroupgap': 0}, - 'template': '...', - 'title': {'text': 'Model sizes in billions of parameters'}, - 'xaxis': {'anchor': 'y', 'domain': [0.0, 1.0], 'title': {'text': 'x'}}, - 'yaxis': {'anchor': 'x', 'domain': [0.0, 1.0], 'title': {'text': 'y'}}} -})",Model sizes in billions of parameters -./html/plots/execution_costs.html,"Figure({ - 'data': [{'alignmentgroup': 'True', - 'hovertemplate': 'color=gpt-3.5-turbo
x=%{x}
y=%{y}', - 'legendgroup': 'gpt-3.5-turbo', - 'marker': {'color': '#636efa', 'pattern': {'shape': ''}}, - 'name': 'gpt-3.5-turbo', - 'offsetgroup': 'gpt-3.5-turbo', - 'orientation': 'v', - 'showlegend': True, - 'textposition': 'auto', - 'type': 'bar', - 'x': array(['gpt-3.5-turbo'], dtype=object), - 'xaxis': 'x', - 'y': array([0.2]), - 'yaxis': 'y'}, - {'alignmentgroup': 'True', - 'hovertemplate': 'color=llama-2-70b-chat
x=%{x}
y=%{y}', - 'legendgroup': 'llama-2-70b-chat', - 'marker': {'color': '#EF553B', 'pattern': {'shape': ''}}, - 'name': 'llama-2-70b-chat', - 'offsetgroup': 'llama-2-70b-chat', - 'orientation': 'v', - 'showlegend': True, - 'textposition': 'auto', - 'type': 'bar', - 'x': array(['llama-2-70b-chat'], dtype=object), - 'xaxis': 'x', - 'y': array([0.03]), - 'yaxis': 'y'}, - {'alignmentgroup': 'True', - 'hovertemplate': 'color=Mixtral-8x7B-Instruct-v0.1
x=%{x}
y=%{y}', - 'legendgroup': 'Mixtral-8x7B-Instruct-v0.1', - 'marker': {'color': '#00cc96', 'pattern': {'shape': ''}}, - 'name': 'Mixtral-8x7B-Instruct-v0.1', - 'offsetgroup': 'Mixtral-8x7B-Instruct-v0.1', - 'orientation': 'v', - 'showlegend': True, - 'textposition': 'auto', - 'type': 'bar', - 'x': array(['Mixtral-8x7B-Instruct-v0.1'], dtype=object), - 'xaxis': 'x', - 'y': array([0.135]), - 'yaxis': 'y'}, - {'alignmentgroup': 'True', - 'hovertemplate': 'color=zephyr-7b-beta
x=%{x}
y=%{y}', - 'legendgroup': 'zephyr-7b-beta', - 'marker': {'color': '#ab63fa', 'pattern': {'shape': ''}}, - 'name': 'zephyr-7b-beta', - 'offsetgroup': 'zephyr-7b-beta', - 'orientation': 'v', - 'showlegend': True, - 'textposition': 'auto', - 'type': 'bar', - 'x': array(['zephyr-7b-beta'], dtype=object), - 'xaxis': 'x', - 'y': array([55.45703704]), - 'yaxis': 'y'}, - {'alignmentgroup': 'True', - 'hovertemplate': 'color=Mistral-7B-Instruct-v0.2
x=%{x}
y=%{y}', - 'legendgroup': 'Mistral-7B-Instruct-v0.2', - 'marker': {'color': '#FFA15A', 'pattern': {'shape': ''}}, - 'name': 'Mistral-7B-Instruct-v0.2', - 'offsetgroup': 'Mistral-7B-Instruct-v0.2', - 'orientation': 'v', - 'showlegend': True, - 'textposition': 'auto', - 'type': 'bar', - 'x': array(['Mistral-7B-Instruct-v0.2'], dtype=object), - 'xaxis': 'x', - 'y': array([55.45703704]), - 'yaxis': 'y'}, - {'alignmentgroup': 'True', - 'hovertemplate': 'color=TinyLlama/TinyLlama-1.1B-Chat-v1.0
x=%{x}
y=%{y}', - 'legendgroup': 'TinyLlama/TinyLlama-1.1B-Chat-v1.0', - 'marker': {'color': '#19d3f3', 'pattern': {'shape': ''}}, - 'name': 'TinyLlama/TinyLlama-1.1B-Chat-v1.0', - 'offsetgroup': 'TinyLlama/TinyLlama-1.1B-Chat-v1.0', - 'orientation': 'v', - 'showlegend': True, - 'textposition': 'auto', - 'type': 'bar', - 'x': array(['TinyLlama/TinyLlama-1.1B-Chat-v1.0'], dtype=object), - 'xaxis': 'x', - 'y': array([25.59555556]), - 'yaxis': 'y'}, - {'alignmentgroup': 'True', - 'hovertemplate': 'color=gemini-pro
x=%{x}
y=%{y}', - 'legendgroup': 'gemini-pro', - 'marker': {'color': '#FF6692', 'pattern': {'shape': ''}}, - 'name': 'gemini-pro', - 'offsetgroup': 'gemini-pro', - 'orientation': 'v', - 'showlegend': True, - 'textposition': 'auto', - 'type': 'bar', - 'x': array(['gemini-pro'], dtype=object), - 'xaxis': 'x', - 'y': array([0.05]), - 'yaxis': 'y'}], - 'layout': {'barmode': 'relative', - 'legend': {'title': {'text': 'color'}, 'tracegroupgap': 0}, - 'template': '...', - 'title': {'text': 'Costs of execution of a sample query 1000 times'}, - 'xaxis': {'anchor': 'y', 'domain': [0.0, 1.0], 'title': {'text': 'x'}}, - 'yaxis': {'anchor': 'x', 'domain': [0.0, 1.0], 'title': {'text': 'y'}}} -})",Costs of execution of a sample query 1000 times diff --git a/data/2024-01-22 12:14:03.377435_general_plot.csv b/data/2024-01-22 12:14:03.377435_general_plot.csv deleted file mode 100644 index a6294657717d810124b0d8d9a2b22ceea6bd6fef..0000000000000000000000000000000000000000 --- a/data/2024-01-22 12:14:03.377435_general_plot.csv +++ /dev/null @@ -1,6168 +0,0 @@ -model,language,template_name,column,path,plot_object,description -gpt-3.5-turbo,english,json,chunk_sizes,./html/plots/english|json_chunk_sizes.html,"Figure({ - 'data': [{'type': 'scatter', - 'x': [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, - 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, - 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, - 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, - 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, - 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93], - 'y': [1.4, 1.65, 2.8, 4.6, 3.55, 2.6, 3.0, 4.65, 4.25, 5.2, 5.1, - 5.75, 5.5, 6.2, 5.8, 4.55, 4.65, 4.9, 5.2, 4.05, 4.85, 2.95, - 3.9, 3.85, 3.5, 3.0, 3.25, 3.0, 3.1, 3.3, 3.6, 3.95, 3.25, 3.3, - 4.15, 4.15, 4.3, 3.85, 4.65, 3.15, 3.35, 2.05, 3.1, 3.05, 4.6, - 2.6, 4.65, 3.4, 4.1, 3.85, 4.3, 3.6, 3.0, 3.4, 3.6, 3.6, 3.45, - 3.0, 3.789473684210526, 1.9473684210526316, 3.1578947368421053, - 2.7777777777777777, 3.7222222222222223, 4.555555555555555, - 3.888888888888889, 4.055555555555555, 3.6470588235294117, - 4.235294117647059, 4.470588235294118, 3.411764705882353, - 3.1176470588235294, 3.8823529411764706, 3.8823529411764706, - 3.75, 4.875, 3.8125, 4.0625, 3.3125, 4.5625, 2.875, 2.8125, - 4.0, 2.75, 3.8333333333333335, 2.909090909090909, - 3.3636363636363638, 2.4545454545454546, 2.272727272727273, - 1.7777777777777777, 3.142857142857143, 3.142857142857143, - 3.4285714285714284, 1.7142857142857142, 4.0]}], - 'layout': {'template': '...', - 'xaxis': {'title': {'text': 'chunk_index'}}, - 'yaxis': {'title': {'text': 'chunk_sizes'}}} -})",Plot of chunk_sizes for english|json -gpt-3.5-turbo,english,json,chunk_sizes,./html/plots/english|json_chunk_sizes_histogram.html,"Figure({ - 'data': [{'type': 'histogram', - 'x': [2, 1, 7, ..., 1, 1, 1]}], - 'layout': {'template': '...', 'xaxis': {'title': {'text': 'chunk_sizes'}}, 'yaxis': {'title': {'text': 'frequency'}}} -})",Histogram of chunk_sizes for english|json -gpt-3.5-turbo,japanese,markdown,chunk_sizes,./html/plots/japanese|markdown_chunk_sizes.html,"Figure({ - 'data': [{'type': 'scatter', - 'x': [0, 1, 2, ..., 768, 769, 770], - 'y': [1.3, 2.6, 1.6, ..., 1.0, 1.0, 4.0]}], - 'layout': {'template': '...', - 'xaxis': {'title': {'text': 'chunk_index'}}, - 'yaxis': {'title': {'text': 'chunk_sizes'}}} -})",Plot of chunk_sizes for japanese|markdown -gpt-3.5-turbo,japanese,markdown,chunk_sizes,./html/plots/japanese|markdown_chunk_sizes_histogram.html,"Figure({ - 'data': [{'type': 'histogram', - 'x': [1, 1, 1, ..., 1, 1, 4]}], - 'layout': {'template': '...', 'xaxis': {'title': {'text': 'chunk_sizes'}}, 'yaxis': {'title': {'text': 'frequency'}}} -})",Histogram of chunk_sizes for japanese|markdown -gpt-3.5-turbo,english,markdown,chunk_sizes,./html/plots/english|markdown_chunk_sizes.html,"Figure({ - 'data': [{'type': 'scatter', - 'x': [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, - 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, - 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, - 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, - 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, - 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, - 98, 99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, - 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 121, 122, - 123, 124, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, - 135, 136, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146, - 147, 148, 149, 150, 151, 152, 153, 154, 155, 156, 157, 158, - 159, 160, 161, 162, 163, 164, 165, 166, 167], - 'y': [2.65, 3.95, 4.9, 5.0, 5.8, 3.3, 4.7, 5.2, 5.85, 5.2, 4.9, 5.4, - 4.8, 4.6, 6.6, 4.75, 7.05, 5.5, 4.05, 3.15, 3.65, 2.75, 4.1, - 4.05, 3.8, 4.15, 3.3, 6.0, 4.6, 3.85, 4.4, 3.55, 3.3, 2.85, - 2.95, 2.7, 1.95, 2.9, 3.45, 3.0, 3.4, 4.25, 3.95, 3.35, 3.7, - 2.1, 3.65, 3.3, 3.35, 2.3, 2.75, 4.35, 2.15, 3.0, 3.05, 3.65, - 4.1, 3.1, 3.0, 3.6, 3.8, 3.55, 2.7, 3.35, 3.0, 4.45, 3.05, - 3.25, 4.6, 3.8, 4.6, 3.9473684210526314, 3.6315789473684212, - 3.0, 3.4210526315789473, 3.5789473684210527, 3.789473684210526, - 3.5789473684210527, 4.526315789473684, 3.1052631578947367, - 4.052631578947368, 3.736842105263158, 3.7777777777777777, - 4.388888888888889, 3.0, 4.166666666666667, 2.7777777777777777, - 2.888888888888889, 2.7777777777777777, 3.411764705882353, - 4.647058823529412, 3.8823529411764706, 4.4, 3.8181818181818183, - 4.090909090909091, 5.2727272727272725, 4.0, 3.5, 4.1, 4.25, - 3.0, 2.5, 1.0, 5.0, 1.0, 3.0, 1.0, 1.0, 1.0, 1.0, 2.0, 2.0, - 1.0, 1.0, 2.0, 1.0, 1.0, 4.0, 9.0, 1.0, 5.0, 4.0, 12.0, 3.0, - 9.0, 3.0, 3.0, 1.0, 1.0, 1.0, 1.0, 2.0, 3.0, 6.0, 1.0, 4.0, - 6.0, 1.0, 3.0, 3.0, 4.0, 3.0, 3.0, 3.0, 5.0, 3.0, 4.0, 5.0, - 6.0, 5.0, 1.0, 2.0, 2.0, 6.0, 9.0, 3.0, 5.0, 4.0, 5.0, 8.0, - 5.0, 4.0, 7.0, 8.0, 6.0, 3.0, 1.0, 4.0]}], - 'layout': {'template': '...', - 'xaxis': {'title': {'text': 'chunk_index'}}, - 'yaxis': {'title': {'text': 'chunk_sizes'}}} -})",Plot of chunk_sizes for english|markdown -gpt-3.5-turbo,english,markdown,chunk_sizes,./html/plots/english|markdown_chunk_sizes_histogram.html,"Figure({ - 'data': [{'type': 'histogram', - 'x': [3, 4, 7, ..., 3, 4, 9]}], - 'layout': {'template': '...', 'xaxis': {'title': {'text': 'chunk_sizes'}}, 'yaxis': {'title': {'text': 'frequency'}}} -})",Histogram of chunk_sizes for english|markdown -gpt-3.5-turbo,japanese,json,chunk_sizes,./html/plots/japanese|json_chunk_sizes.html,"Figure({ - 'data': [{'type': 'scatter', - 'x': [0, 1, 2, ..., 341, 342, 343], - 'y': [1.4, 1.6, 4.0, ..., 1.0, 2.0, 1.0]}], - 'layout': {'template': '...', - 'xaxis': {'title': {'text': 'chunk_index'}}, - 'yaxis': {'title': {'text': 'chunk_sizes'}}} -})",Plot of chunk_sizes for japanese|json -gpt-3.5-turbo,japanese,json,chunk_sizes,./html/plots/japanese|json_chunk_sizes_histogram.html,"Figure({ - 'data': [{'type': 'histogram', - 'x': [2, 1, 7, ..., 2, 1, 4]}], - 'layout': {'template': '...', 'xaxis': {'title': {'text': 'chunk_sizes'}}, 'yaxis': {'title': {'text': 'frequency'}}} -})",Histogram of chunk_sizes for japanese|json -gpt-3.5-turbo,english,json,chunk_generation_times,./html/plots/english|json_chunk_generation_times.html,"Figure({ - 'data': [{'type': 'scatter', - 'x': [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, - 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, - 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, - 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, - 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, - 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93], - 'y': [0.10046198368072509, 0.03240053653717041, - 0.024858307838439942, 0.02590036392211914, - 0.015090155601501464, 0.014921844005584717, - 0.041783690452575684, 0.015995442867279053, - 0.020570504665374755, 0.02352551221847534, - 0.014742863178253175, 0.018694496154785155, - 0.02277406454086304, 0.0202506422996521, 0.023777151107788087, - 0.021399533748626708, 0.01908172369003296, 0.01889885663986206, - 0.030153179168701173, 0.0225541353225708, 0.025065648555755615, - 0.017707681655883788, 0.01762690544128418, - 0.024600279331207276, 0.02091813087463379, - 0.020982897281646727, 0.024668455123901367, - 0.01819167137145996, 0.021642518043518067, 0.02440897226333618, - 0.01764235496520996, 0.02233234643936157, 0.019897449016571044, - 0.022547733783721925, 0.01778780221939087, - 0.022352051734924317, 0.0228739857673645, 0.017243289947509767, - 0.024185216426849364, 0.020494675636291503, - 0.017257440090179443, 0.025904011726379395, - 0.018434965610504152, 0.025427448749542236, - 0.026230669021606444, 0.0218292236328125, 0.017258453369140624, - 0.020304083824157715, 0.025457596778869628, - 0.021047306060791016, 0.020934593677520753, - 0.017962396144866943, 0.030893766880035402, - 0.02429497241973877, 0.015818464756011962, 0.02182251214981079, - 0.017441165447235108, 0.02267346382141113, - 0.021955339532149464, 0.02096122189571983, 0.0219482748132003, - 0.027302728758917913, 0.024971723556518555, - 0.01800923877292209, 0.020341939396328397, - 0.021999557813008625, 0.022776225033928368, - 0.026406035703771254, 0.023925683077643898, - 0.018816204632029813, 0.02561175121980555, - 0.017753348631017348, 0.01904933592852424, - 0.031710803508758545, 0.019595131278038025, - 0.01860131323337555, 0.02681751549243927, 0.019831329584121704, - 0.024308815598487854, 0.028108596801757812, - 0.01862257719039917, 0.02156209945678711, 0.018936177094777424, - 0.021108508110046387, 0.020750804380937057, - 0.030380335721102627, 0.020772327076305042, - 0.020700302991000088, 0.026708364486694336, - 0.02281052725655692, 0.02364325523376465, 0.02599930763244629, - 0.025099686213902066, 0.017879009246826172]}], - 'layout': {'template': '...', - 'xaxis': {'title': {'text': 'chunk_index'}}, - 'yaxis': {'title': {'text': 'chunk_generation_times'}}} -})",Plot of chunk_generation_times for english|json -gpt-3.5-turbo,english,json,chunk_generation_times,./html/plots/english|json_chunk_generation_times_histogram.html,"Figure({ - 'data': [{'type': 'histogram', - 'x': [0.06530380249023438, 0.00109100341796875, - 0.0009443759918212891, ..., 0.0182192325592041, - 0.012401819229125977, 0.015912532806396484]}], - 'layout': {'template': '...', - 'xaxis': {'title': {'text': 'chunk_generation_times'}}, - 'yaxis': {'title': {'text': 'frequency'}}} -})",Histogram of chunk_generation_times for english|json -gpt-3.5-turbo,japanese,markdown,chunk_generation_times,./html/plots/japanese|markdown_chunk_generation_times.html,"Figure({ - 'data': [{'type': 'scatter', - 'x': [0, 1, 2, ..., 768, 769, 770], - 'y': [0.10856695175170898, 0.027323269844055177, - 0.0005894899368286133, ..., 0.027635812759399414, - 0.035398006439208984, 0.0004639625549316406]}], - 'layout': {'template': '...', - 'xaxis': {'title': {'text': 'chunk_index'}}, - 'yaxis': {'title': {'text': 'chunk_generation_times'}}} -})",Plot of chunk_generation_times for japanese|markdown -gpt-3.5-turbo,japanese,markdown,chunk_generation_times,./html/plots/japanese|markdown_chunk_generation_times_histogram.html,"Figure({ - 'data': [{'type': 'histogram', - 'x': [0.09664440155029297, 0.0009276866912841797, - 0.0006921291351318359, ..., 0.027635812759399414, - 0.035398006439208984, 0.0004639625549316406]}], - 'layout': {'template': '...', - 'xaxis': {'title': {'text': 'chunk_generation_times'}}, - 'yaxis': {'title': {'text': 'frequency'}}} -})",Histogram of chunk_generation_times for japanese|markdown -gpt-3.5-turbo,english,markdown,chunk_generation_times,./html/plots/english|markdown_chunk_generation_times.html,"Figure({ - 'data': [{'type': 'scatter', - 'x': [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, - 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, - 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, - 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, - 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, - 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, - 98, 99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, - 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 121, 122, - 123, 124, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, - 135, 136, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146, - 147, 148, 149, 150, 151, 152, 153, 154, 155, 156, 157, 158, - 159, 160, 161, 162, 163, 164, 165, 166, 167], - 'y': [0.09208251237869262, 0.026124024391174318, - 0.01616170406341553, 0.02852156162261963, 0.014723885059356689, - 0.020538461208343507, 0.029323899745941163, - 0.016685795783996583, 0.01502150297164917, - 0.032468545436859134, 0.023004639148712158, - 0.018346405029296874, 0.024369895458221436, - 0.02129126787185669, 0.02636735439300537, 0.028070759773254395, - 0.015048229694366455, 0.018386292457580566, - 0.024474453926086426, 0.02241969108581543, 0.02212299108505249, - 0.02697488069534302, 0.018822431564331055, - 0.022496461868286133, 0.02287602424621582, - 0.014856135845184327, 0.018757724761962892, 0.0360129714012146, - 0.02094881534576416, 0.020023763179779053, - 0.023487961292266844, 0.02022104263305664, - 0.021625709533691407, 0.026040089130401612, - 0.01464219093322754, 0.020658397674560548, - 0.022537052631378174, 0.02016826868057251, - 0.023719727993011475, 0.021998834609985352, - 0.014762508869171142, 0.020593512058258056, - 0.031562745571136475, 0.01942124366760254, - 0.018172550201416015, 0.026357293128967285, - 0.014737892150878906, 0.02184560298919678, 0.02521200180053711, - 0.0145959734916687, 0.019272708892822267, 0.02345912456512451, - 0.018707871437072754, 0.02064570188522339, - 0.026726770401000976, 0.014578986167907714, - 0.02704044580459595, 0.0275115966796875, 0.017576706409454346, - 0.02309427261352539, 0.021034085750579835, 0.02014453411102295, - 0.02423384189605713, 0.019620859622955324, - 0.015612244606018066, 0.019633555412292482, - 0.023806488513946532, 0.029540610313415528, - 0.018076753616333006, 0.020523488521575928, - 0.018189358711242675, 0.019011936689677992, - 0.025250146263524106, 0.01884603500366211, - 0.027890945735730623, 0.017041005586322985, - 0.02217518655877364, 0.02624903227153577, 0.017062714225367495, - 0.02720752515290913, 0.035589167946263364, - 0.016492429532502826, 0.022044658660888672, - 0.02782448132832845, 0.018842458724975586, 0.02544562021891276, - 0.023582816123962402, 0.0199509859085083, 0.0204342868593004, - 0.019165529924280503, 0.017221310559441063, - 0.02155288527993595, 0.021391789118448894, - 0.025321657007390804, 0.01995407451282848, - 0.020000804554332386, 0.027066252448342064, - 0.028322601318359376, 0.020383334159851073, - 0.01763775944709778, 0.019829511642456055, - 0.018830597400665283, 0.0003197193145751953, - 0.0002859830856323242, 0.037157535552978516, - 0.0003559589385986328, 0.00033020973205566406, - 0.00030481815338134766, 0.0003345012664794922, - 0.0378338098526001, 0.0003420114517211914, - 0.0004042387008666992, 0.00030684471130371094, - 0.0003019571304321289, 0.03824722766876221, - 0.000339508056640625, 0.0003319978713989258, - 0.00029850006103515625, 0.00029754638671875, - 0.12906873226165771, 0.04114532470703125, - 0.00035190582275390625, 0.04018056392669678, - 0.04078686237335205, 0.0003370046615600586, - 0.040924787521362305, 0.03983438014984131, - 0.0003578662872314453, 0.0003381967544555664, - 0.00032329559326171875, 0.0003101825714111328, - 0.04037809371948242, 0.0003516674041748047, - 0.0003418922424316406, 0.00031316280364990234, - 0.0003008842468261719, 0.03879415988922119, - 0.0003923177719116211, 0.000377655029296875, - 0.0003113746643066406, 0.0003039836883544922, - 0.039052486419677734, 0.00037670135498046875, - 0.0003503561019897461, 0.00037550926208496094, - 0.0003299713134765625, 0.03934800624847412, - 0.0010035037994384766, 0.0003172159194946289, - 0.03936612606048584, 0.04538893699645996, - 0.00036203861236572266, 0.00033092498779296875, - 0.00031876564025878906, 0.035516977310180664, - 0.038269758224487305, 0.00031638145446777344, - 0.0002728700637817383, 0.03825116157531738, - 0.03864848613739014, 0.03890562057495117, 0.04098498821258545, - 0.0005698204040527344, 0.0005306005477905273, - 0.036808133125305176, 0.04005300998687744, 0.0428234338760376, - 0.0005092620849609375]}], - 'layout': {'template': '...', - 'xaxis': {'title': {'text': 'chunk_index'}}, - 'yaxis': {'title': {'text': 'chunk_generation_times'}}} -})",Plot of chunk_generation_times for english|markdown -gpt-3.5-turbo,english,markdown,chunk_generation_times,./html/plots/english|markdown_chunk_generation_times_histogram.html,"Figure({ - 'data': [{'type': 'histogram', - 'x': [0.06274151802062988, 0.0009312629699707031, - 0.0006353855133056641, ..., 0.011092424392700195, - 0.011125326156616211, 0.014921903610229492]}], - 'layout': {'template': '...', - 'xaxis': {'title': {'text': 'chunk_generation_times'}}, - 'yaxis': {'title': {'text': 'frequency'}}} -})",Histogram of chunk_generation_times for english|markdown -gpt-3.5-turbo,japanese,json,chunk_generation_times,./html/plots/japanese|json_chunk_generation_times.html,"Figure({ - 'data': [{'type': 'scatter', - 'x': [0, 1, 2, ..., 341, 342, 343], - 'y': [0.03325941562652588, 0.022845458984375, 0.008539342880249023, - ..., 0.01340627670288086, 0.0009033679962158203, - 0.0009148120880126953]}], - 'layout': {'template': '...', - 'xaxis': {'title': {'text': 'chunk_index'}}, - 'yaxis': {'title': {'text': 'chunk_generation_times'}}} -})",Plot of chunk_generation_times for japanese|json -gpt-3.5-turbo,japanese,json,chunk_generation_times,./html/plots/japanese|json_chunk_generation_times_histogram.html,"Figure({ - 'data': [{'type': 'histogram', - 'x': [0.055197715759277344, 0.0009396076202392578, - 0.0006830692291259766, ..., 0.09629225730895996, - 0.0002498626708984375, 0.02581787109375]}], - 'layout': {'template': '...', - 'xaxis': {'title': {'text': 'chunk_generation_times'}}, - 'yaxis': {'title': {'text': 'frequency'}}} -})",Histogram of chunk_generation_times for japanese|json -gpt-3.5-turbo,english,json,chunk_generation_times_by_chunk_sizes,./html/plots/english|json_chunk_generation_times_by_chunk_sizes.html,"Figure({ - 'data': [{'type': 'scatter', - 'x': [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, - 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, - 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, - 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, - 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, - 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93], - 'y': [0.08881364862124125, 0.012830307015350886, - 0.0064611540332673075, 0.0030427001522044944, - 0.0012172913284965487, 0.0010328626803360436, - 0.002154427544347976, 0.0008185346057660483, - 0.0008266825447255308, 0.000760871848028172, - 0.00045842723370057606, 0.00046171496183959924, - 0.00047127716587811477, 0.00038408483282244944, - 0.0003980975856065783, 0.0003487464370932618, - 0.0002965170545073433, 0.0002700690074389441, - 0.00037837427634977207, 0.0002866590783409241, - 0.00029493569297919835, 0.00020610502551212962, - 0.0002056610358036507, 0.0002556709545080788, - 0.00021863463385897843, 0.0002219719517650634, - 0.00024266534764616813, 0.00017596374882596956, - 0.00020285578972633502, 0.00021708531685676584, - 0.0001548711550720346, 0.00018800492851703547, - 0.00015937359887022992, 0.00017812613615565616, - 0.0001415090139225613, 0.00016561077338479954, - 0.00016583709916750757, 0.00012602757341873813, - 0.00016227505976302718, 0.00013630295275824343, - 0.00011568545287166481, 0.000161301372429186, - 0.00011680775120967695, 0.00015618929982248828, - 0.0001531285078796367, 0.00013086565473866444, - 0.0001005047225825474, 0.00011247224608928101, - 0.0001386543480009729, 0.00011219802282768186, - 0.0001064520749112099, 9.064017950346037e-05, - 0.00015197036174066016, 0.00011933885090705775, - 7.726775757721345e-05, 0.00010199303274006767, - 8.038324391604707e-05, 0.00010754656963653864, - 9.890817006997501e-05, 9.641565009028522e-05, - 9.889980322311977e-05, 0.00011965482689836298, - 0.00011026073189590966, 7.68795829726359e-05, - 8.488755457789014e-05, 9.2034010611518e-05, - 9.30288186306384e-05, 0.00010473556974214237, - 9.396757780640082e-05, 7.280453944623646e-05, - 9.839988391097912e-05, 6.629642442848702e-05, - 7.012915942254425e-05, 0.00011638762448193335, - 7.01056800013593e-05, 6.539925829258799e-05, - 9.312883553243395e-05, 6.794533329217034e-05, - 8.297807489765248e-05, 9.471462087460092e-05, - 6.133946290140733e-05, 7.026849327649994e-05, - 5.961504138096624e-05, 6.563258693968294e-05, - 6.383154896123252e-05, 9.528001542696267e-05, - 6.246172585711863e-05, 6.181504461999184e-05, - 7.949675912702044e-05, 6.619173043054431e-05, - 6.797917138507241e-05, 7.434168847616238e-05, - 7.122499242952558e-05, 5.27404402561244e-05]}], - 'layout': {'template': '...', - 'xaxis': {'title': {'text': 'chunk_index'}}, - 'yaxis': {'title': {'text': 'chunk_generation_times_by_chunk_sizes'}}} -})",Plot of chunk_generation_times_by_chunk_sizes for english|json -gpt-3.5-turbo,english,json,chunk_generation_times_by_chunk_sizes,./html/plots/english|json_chunk_generation_times_by_chunk_sizes_histogram.html,"Figure({ - 'data': [{'type': 'histogram', - 'x': [0.03265190124511719, 0.0003636678059895833, - 9.443759918212891e-05, ..., 5.2354116549437074e-05, - 3.553529865079076e-05, 4.5464379446847095e-05]}], - 'layout': {'template': '...', - 'xaxis': {'title': {'text': 'chunk_generation_times_by_chunk_sizes'}}, - 'yaxis': {'title': {'text': 'frequency'}}} -})",Histogram of chunk_generation_times_by_chunk_sizes for english|json -gpt-3.5-turbo,japanese,markdown,chunk_generation_times_by_chunk_sizes,./html/plots/japanese|markdown_chunk_generation_times_by_chunk_sizes.html,"Figure({ - 'data': [{'type': 'scatter', - 'x': [0, 1, 2, ..., 768, 769, 770], - 'y': [0.10252033472061158, 0.005723926850727626, - 0.00015428165594736734, ..., 3.4893702979039664e-05, - 4.463809134830893e-05, 5.821362044311677e-07]}], - 'layout': {'template': '...', - 'xaxis': {'title': {'text': 'chunk_index'}}, - 'yaxis': {'title': {'text': 'chunk_generation_times_by_chunk_sizes'}}} -})",Plot of chunk_generation_times_by_chunk_sizes for japanese|markdown -gpt-3.5-turbo,japanese,markdown,chunk_generation_times_by_chunk_sizes,./html/plots/japanese|markdown_chunk_generation_times_by_chunk_sizes_histogram.html,"Figure({ - 'data': [{'type': 'histogram', - 'x': [0.09664440155029297, 0.00046384334564208984, - 0.00023070971171061197, ..., 3.4893702979039664e-05, - 4.463809134830893e-05, 5.821362044311677e-07]}], - 'layout': {'template': '...', - 'xaxis': {'title': {'text': 'chunk_generation_times_by_chunk_sizes'}}, - 'yaxis': {'title': {'text': 'frequency'}}} -})",Histogram of chunk_generation_times_by_chunk_sizes for japanese|markdown -gpt-3.5-turbo,english,markdown,chunk_generation_times_by_chunk_sizes,./html/plots/english|markdown_chunk_generation_times_by_chunk_sizes.html,"Figure({ - 'data': [{'type': 'scatter', - 'x': [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, - 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, - 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, - 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, - 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, - 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, - 98, 99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, - 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 121, 122, - 123, 124, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, - 135, 136, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146, - 147, 148, 149, 150, 151, 152, 153, 154, 155, 156, 157, 158, - 159, 160, 161, 162, 163, 164, 165, 166, 167], - 'y': [0.03632562756538391, 0.0041558427611986795, - 0.0015482904225544842, 0.001825864957524585, - 0.0008218889501803647, 0.000929749278026769, - 0.0010206748414825178, 0.0005587356991541535, - 0.0004158333411608837, 0.0007294862860957942, - 0.0005001733624220186, 0.00034631598065473036, - 0.00040755672467626827, 0.0003383196497622263, - 0.0003800022888386437, 0.00035712016487067196, - 0.00019103740172862242, 0.000218210582249543, - 0.00026796686353620686, 0.00023573625600167053, - 0.0002323285202751794, 0.00026580079774429386, - 0.00017241300318212942, 0.00021267361273871947, - 0.0002016752708531258, 0.0001309303547095743, - 0.00015869303614781739, 0.00026248786388367363, - 0.00016811253463466544, 0.00015285407199782197, - 0.00016983772856239, 0.00014906236564247413, - 0.00014580468267572224, 0.0001798519244119315, - 0.00010193680908334596, 0.00013948870924051696, - 0.00014732003932834737, 0.00012420512763942562, - 0.00015552588294370082, 0.00013642120079356855, - 9.279294113447869e-05, 0.00012410135881899386, - 0.00017717047952708328, 0.00011449380917642991, - 0.00010220058833488828, 0.0001417657532181025, - 8.147143102416876e-05, 0.00011272820802376782, - 0.00013282181558725903, 7.679730910306085e-05, - 9.789502667772756e-05, 0.00011335508502119439, - 8.829357089929674e-05, 0.00010367267611149014, - 0.00012067089010691825, 7.01513324933404e-05, - 0.00012273148858170195, 0.00011814963883815212, - 8.107124991382932e-05, 0.00010006237447860349, - 9.044187934664484e-05, 8.961044588314943e-05, - 9.811671195620328e-05, 8.126747041158346e-05, - 6.573715673389812e-05, 7.863378246974325e-05, - 9.551787039155241e-05, 0.00011430785201089551, - 7.016163336196306e-05, 8.012737695460754e-05, - 6.826918517944221e-05, 7.0438192818372e-05, - 8.969769308821329e-05, 6.837849595508661e-05, - 9.846763872844533e-05, 6.10720910246614e-05, - 7.478768011964158e-05, 8.663701706745981e-05, - 5.81746144180273e-05, 8.932049205458166e-05, - 0.00011453196496396676, 5.5263752787186024e-05, - 6.936049506852808e-05, 8.769330826921082e-05, - 5.9844635253995374e-05, 8.124097379450256e-05, - 7.445598390489517e-05, 6.141147240032585e-05, - 6.16378090714557e-05, 5.856617861823866e-05, - 5.3039432746347645e-05, 6.564544623331413e-05, - 6.453609817836689e-05, 6.968950336014621e-05, - 5.723248678470528e-05, 5.6514190443413204e-05, - 7.545989961151253e-05, 7.464698045814285e-05, - 5.593965934784983e-05, 4.937732527848694e-05, - 4.375327639145874e-05, 5.000265807728637e-05, - 7.011388477526213e-07, 6.203537649291198e-07, - 8.042756613198813e-05, 7.655030937605007e-07, - 7.08604575226747e-07, 6.527155318658408e-07, - 7.147462958963508e-07, 8.066910416332644e-05, - 7.261389633146315e-07, 8.546272745596178e-07, - 6.473517116112046e-07, 6.356992219623766e-07, - 8.018286723010945e-05, 7.102679009218097e-07, - 6.931062033380497e-07, 6.180125487270315e-07, - 6.047690786966463e-07, 0.00026180270235630365, - 8.262113394986195e-05, 7.01007615047622e-07, - 7.817230335933225e-05, 7.889141658288599e-05, - 6.406932729278681e-07, 7.736254729936163e-05, - 7.487665441699494e-05, 6.714189253873271e-07, - 6.333272555347685e-07, 6.042908285265771e-07, - 5.786988272595762e-07, 7.505221880944688e-05, - 6.500321703785669e-07, 6.250315218128713e-07, - 5.714649701640554e-07, 5.450801572937897e-07, - 6.952358403086235e-05, 7.018207010941344e-07, - 6.719840378947953e-07, 5.511056005427268e-07, - 5.342419830483167e-07, 6.827357765677925e-05, - 6.551327912703805e-07, 6.061524255877961e-07, - 6.440982196997616e-07, 5.630909786289463e-07, - 6.669153601436292e-05, 1.6865610074596244e-06, - 5.278135099744242e-07, 6.496060406020766e-05, - 7.477584348675447e-05, 5.944804800750783e-07, - 5.416120913141878e-07, 5.166379906949579e-07, - 5.6736385479521825e-05, 6.084222293241225e-05, - 4.990243761321347e-07, 4.276960247362669e-07, - 5.948858720889173e-05, 5.936787425098331e-05, - 5.9307348437425566e-05, 6.209846698876584e-05, - 8.543034543519255e-07, 7.860748856155961e-07, - 5.405012206359057e-05, 5.855703214455766e-05, - 6.251596186282861e-05, 7.391321987822025e-07]}], - 'layout': {'template': '...', - 'xaxis': {'title': {'text': 'chunk_index'}}, - 'yaxis': {'title': {'text': 'chunk_generation_times_by_chunk_sizes'}}} -})",Plot of chunk_generation_times_by_chunk_sizes for english|markdown -gpt-3.5-turbo,english,markdown,chunk_generation_times_by_chunk_sizes,./html/plots/english|markdown_chunk_generation_times_by_chunk_sizes_histogram.html,"Figure({ - 'data': [{'type': 'histogram', - 'x': [0.02091383934020996, 0.00013303756713867188, - 4.538467952183315e-05, ..., 3.7348230278451834e-05, - 3.696121646716349e-05, 4.813517293622417e-05]}], - 'layout': {'template': '...', - 'xaxis': {'title': {'text': 'chunk_generation_times_by_chunk_sizes'}}, - 'yaxis': {'title': {'text': 'frequency'}}} -})",Histogram of chunk_generation_times_by_chunk_sizes for english|markdown -gpt-3.5-turbo,japanese,json,chunk_generation_times_by_chunk_sizes,./html/plots/japanese|json_chunk_generation_times_by_chunk_sizes.html,"Figure({ - 'data': [{'type': 'scatter', - 'x': [0, 1, 2, ..., 341, 342, 343], - 'y': [0.024574017524719237, 0.007615152994791666, - 0.0016790103912353517, ..., 3.455225954350737e-05, - 2.31632819542518e-06, 2.339672859367507e-06]}], - 'layout': {'template': '...', - 'xaxis': {'title': {'text': 'chunk_index'}}, - 'yaxis': {'title': {'text': 'chunk_generation_times_by_chunk_sizes'}}} -})",Plot of chunk_generation_times_by_chunk_sizes for japanese|json -gpt-3.5-turbo,japanese,json,chunk_generation_times_by_chunk_sizes,./html/plots/japanese|json_chunk_generation_times_by_chunk_sizes_histogram.html,"Figure({ - 'data': [{'type': 'histogram', - 'x': [0.027598857879638672, 0.0003132025400797526, - 6.830692291259766e-05, ..., 0.00011829515639921371, - 3.0657996429256133e-07, 3.152365212912088e-05]}], - 'layout': {'template': '...', - 'xaxis': {'title': {'text': 'chunk_generation_times_by_chunk_sizes'}}, - 'yaxis': {'title': {'text': 'frequency'}}} -})",Histogram of chunk_generation_times_by_chunk_sizes for japanese|json -gpt-3.5-turbo,english,json,"chunk_sizes, chunk_generation_times",./html/plots/english|json_scatter.html,"Figure({ - 'data': [{'mode': 'markers', - 'name': 'Sample 4', - 'type': 'scatter', - 'x': [2, 1, 7, 2, 2, 3, 4, 7, 4, 7, 2, 7, 8, 8, 4, 5, 3, 6, 4, 8, 9, - 5, 10, 8, 6, 9, 10, 1, 7, 5, 1, 3, 3, 3, 1, 2, 3, 4, 6, 3, 3, - 4, 4, 6, 1, 6, 5, 6, 8, 1, 8, 11, 3, 7, 4, 6, 3, 1], - 'y': [0.06530380249023438, 0.00109100341796875, - 0.0009443759918212891, 0.06685900688171387, - 0.001277923583984375, 0.0010423660278320312, - 0.053321123123168945, 0.001285552978515625, - 0.0011181831359863281, 0.03932929039001465, - 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0.001096963882446289, 0.016451358795166016, - 0.0012264251708984375, 0.0010192394256591797]}, - {'mode': 'markers', - 'name': 'Sample 5', - 'type': 'scatter', - 'x': [2, 1, 7, 2, 2, 3, 5, 10, 4, 9, 2, 4, 7, 7, 7, 1, 6, 5, 8, 7, - 3, 4, 9, 7, 7, 7, 5, 5, 1, 5, 7, 3, 1, 2, 1, 1, 1, 5, 1, 7, 1, - 1, 1, 3, 7, 1, 4, 4, 4, 11, 3, 9, 12, 4, 1, 1, 1, 3, 6, 3, 1], - 'y': [0.05827736854553223, 0.001672983169555664, - 0.0011780261993408203, 0.06685996055603027, - 0.0014088153839111328, 0.0011448860168457031, - 0.06088089942932129, 0.0013549327850341797, - 0.001104593276977539, 0.06842279434204102, - 0.001180410385131836, 0.0012087821960449219, - 0.05153369903564453, 0.001417398452758789, - 0.0009801387786865234, 0.0599210262298584, - 0.0018734931945800781, 0.0012083053588867188, - 0.05765342712402344, 0.000926971435546875, - 0.0008299350738525391, 0.06158757209777832, - 0.0007574558258056641, 0.0005726814270019531, - 0.057509660720825195, 0.0008001327514648438, - 0.0004994869232177734, 0.06733345985412598, - 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{'mode': 'markers', 'name': 'Sample 3', 'type': 'scatter', 'x': [], 'y': []}], - 'layout': {'template': '...', - 'xaxis': {'title': {'text': 'chunk_sizes'}}, - 'yaxis': {'title': {'text': 'chunk_generation_times'}}} -})",Scatter plot of chunk_sizes and chunk_generation_times for japanese|markdown -gpt-3.5-turbo,japanese,markdown,"chunk_sizes, chunk_generation_times",./html/plots/japanese|markdown_hist2d.html,"Figure({ - 'data': [{'colorscale': [[0.0, '#440154'], [0.1111111111111111, '#482878'], - [0.2222222222222222, '#3e4989'], [0.3333333333333333, - '#31688e'], [0.4444444444444444, '#26828e'], - [0.5555555555555556, '#1f9e89'], [0.6666666666666666, - '#35b779'], [0.7777777777777778, '#6ece58'], - [0.8888888888888888, '#b5de2b'], [1.0, '#fde725']], - 'name': 'Sample 2', - 'type': 'histogram2d', - 'x': [1, 1, 1, ..., 1, 1, 1], - 'y': [0.09664440155029297, 0.0009276866912841797, - 0.0006921291351318359, ..., 0.01478886604309082, - 0.0007951259613037109, 0.0006318092346191406]}, - {'colorscale': [[0.0, '#440154'], [0.1111111111111111, '#482878'], - 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'template': '...', - 'xaxis': {'title': {'text': 'chunk_sizes'}}, - 'yaxis': {'title': {'text': 'chunk_generation_times'}}} -})",2D histogram of chunk_sizes and chunk_generation_times for japanese|markdown -gpt-3.5-turbo,english,markdown,"chunk_sizes, chunk_generation_times",./html/plots/english|markdown_scatter.html,"Figure({ - 'data': [{'mode': 'markers', - 'name': 'Sample 0', - 'type': 'scatter', - 'x': [3, 4, 7, 4, 7, 2, 7, 8, 8, 4, 5, 3, 6, 4, 8, 9, 5, 1, 2, 1, 2, - 4, 3, 10, 8, 1, 5, 8, 5, 7, 3, 6, 6, 1, 2, 1, 2, 3, 9, 1, 7, 5, - 1, 3, 5, 1, 9, 7, 3, 1, 2, 3, 2, 2, 2, 1, 1, 4, 12, 3, 3, 1, 2, - 3, 3, 3, 4, 4, 6, 1, 4, 9, 1, 6, 5, 6, 4, 3, 3, 3, 8, 1, 5, 8, - 4, 8, 7, 4, 6, 6, 12, 1], - 'y': [0.06274151802062988, 0.0009312629699707031, - 0.0006353855133056641, 0.0561068058013916, - 0.0007245540618896484, 0.0006659030914306641, - 0.05930495262145996, 0.0008580684661865234, - 0.0006489753723144531, 0.058847904205322266, - 0.0008411407470703125, 0.0006690025329589844, - 0.05553746223449707, 0.0009059906005859375, - 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'#31688e'], [0.4444444444444444, '#26828e'], - [0.5555555555555556, '#1f9e89'], [0.6666666666666666, - '#35b779'], [0.7777777777777778, '#6ece58'], - [0.8888888888888888, '#b5de2b'], [1.0, '#fde725']], - 'name': 'Sample 6', - 'type': 'histogram2d', - 'x': [1, 2, 2, ..., 2, 1, 4], - 'y': [0.0005891323089599609, 0.028038740158081055, - 0.000392913818359375, ..., 0.028148651123046875, - 0.0002646446228027344, 0.03060460090637207]}, - {'colorscale': [[0.0, '#440154'], [0.1111111111111111, '#482878'], - [0.2222222222222222, '#3e4989'], [0.3333333333333333, - '#31688e'], [0.4444444444444444, '#26828e'], - [0.5555555555555556, '#1f9e89'], [0.6666666666666666, - '#35b779'], [0.7777777777777778, '#6ece58'], - [0.8888888888888888, '#b5de2b'], [1.0, '#fde725']], - 'name': 'Sample 7', - 'type': 'histogram2d', - 'x': [1, 2, 2, 7, 3, 3, 2, 5, 1, 4, 8, 8, 1, 10, 4, 8, 4, 4, 4, 3, - 3, 6, 3, 2, 10, 5, 7, 4, 4, 9, 3, 4, 14, 7, 3, 7, 1, 1, 13, 3, - 4, 13, 9, 1, 3, 5, 7, 5, 6, 4, 2, 11, 4, 11, 13, 3, 7, 1, 4, 5, - 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0.025934457778930664, 0.00039005279541015625, - 0.0003876686096191406, 0.00036644935607910156, - 0.028306007385253906, 0.029933691024780273, - 0.028206586837768555, 0.00030112266540527344, - 0.00030612945556640625, 0.0002853870391845703, - 0.0002799034118652344, 0.02181696891784668, - 0.02659320831298828, 0.0004444122314453125, - 0.00041174888610839844, 0.025601625442504883, - 0.0004436969757080078, 0.025884151458740234, - 0.00025177001953125, 0.025900840759277344, - 0.0002994537353515625, 0.026368141174316406, - 0.033258676528930664, 0.02091526985168457, - 0.00032639503479003906, 0.02819061279296875, - 0.032218217849731445, 0.032878875732421875, - 0.025840282440185547, 0.0002834796905517578, - 0.00027298927307128906, 0.024205446243286133, - 0.028986692428588867, 0.028474807739257812, - 0.02884078025817871, 0.029344558715820312, 0.00032806396484375, - 0.8321197032928467, 0.11529827117919922, - 0.00037670135498046875, 0.03618359565734863, - 0.02410602569580078, 0.026417970657348633, 0.02703404426574707, - 0.0002582073211669922, 0.0002529621124267578, - 0.02537059783935547, 0.00023984909057617188, - 0.0002999305725097656, 0.02795124053955078, - 0.00027632713317871094, 0.00025391578674316406, - 0.02383279800415039, 0.026427507400512695, - 0.00024199485778808594, 0.026572704315185547, - 0.0002646446228027344, 0.030622005462646484, - 0.027520179748535156, 0.0002906322479248047, - 0.028397798538208008, 0.028812170028686523, - 0.00024962425231933594, 0.028564929962158203, - 0.00024700164794921875, 0.028349637985229492, - 0.00022983551025390625, 0.00022292137145996094, - 0.00021123886108398438, 0.02746129035949707, - 0.00025725364685058594, 0.028192996978759766, - 0.029308080673217773, 0.0002727508544921875, - 0.00022745132446289062, 0.02719902992248535, - 0.028658628463745117, 0.00021576881408691406, - 0.028740644454956055, 0.029018640518188477, - 0.02878594398498535, 0.029675960540771484, - 0.00026917457580566406, 0.026999235153198242, - 0.0003249645233154297, 0.02818155288696289, - 0.028641462326049805, 0.10118842124938965, - 0.0002884864807128906, 0.020873546600341797, - 0.0002846717834472656, 0.00028228759765625, - 0.02573394775390625, 0.0002808570861816406, - 0.0002586841583251953, 0.02629709243774414, - 0.026124000549316406, 0.026563167572021484, 0.0261533260345459, - 0.00021386146545410156, 0.027230501174926758, - 0.025519132614135742, 0.00022077560424804688, - 0.029922962188720703, 0.028708934783935547, - 0.03158760070800781, 0.0256502628326416, 0.02868175506591797, - 0.03081512451171875, 0.02991509437561035, 0.028234243392944336, - 0.00022482872009277344, 0.00021791458129882812, - 0.03341245651245117, 0.026630640029907227, - 0.034381866455078125, 0.02265191078186035, - 0.00022912025451660156, 0.0002181529998779297, - 0.028269529342651367, 0.028667688369750977, - 0.09629225730895996, 0.0002498626708984375, 0.02581787109375]}, - {'colorscale': [[0.0, '#440154'], [0.1111111111111111, '#482878'], - [0.2222222222222222, '#3e4989'], [0.3333333333333333, - '#31688e'], [0.4444444444444444, '#26828e'], - [0.5555555555555556, '#1f9e89'], [0.6666666666666666, - '#35b779'], [0.7777777777777778, '#6ece58'], - [0.8888888888888888, '#b5de2b'], [1.0, '#fde725']], - 'name': 'Sample 6', - 'type': 'histogram2d', - 'x': [], - 'y': []}, - {'colorscale': [[0.0, '#440154'], [0.1111111111111111, '#482878'], - [0.2222222222222222, '#3e4989'], [0.3333333333333333, - '#31688e'], [0.4444444444444444, '#26828e'], - [0.5555555555555556, '#1f9e89'], [0.6666666666666666, - '#35b779'], [0.7777777777777778, '#6ece58'], - [0.8888888888888888, '#b5de2b'], [1.0, '#fde725']], - 'name': 'Sample 7', - 'type': 'histogram2d', - 'x': [], - 'y': []}, - {'colorscale': [[0.0, '#440154'], [0.1111111111111111, '#482878'], - [0.2222222222222222, '#3e4989'], [0.3333333333333333, - '#31688e'], [0.4444444444444444, '#26828e'], - [0.5555555555555556, '#1f9e89'], [0.6666666666666666, - '#35b779'], [0.7777777777777778, '#6ece58'], - [0.8888888888888888, '#b5de2b'], [1.0, '#fde725']], - 'name': 'Sample 6', - 'type': 'histogram2d', - 'x': [], - 'y': []}, - {'colorscale': [[0.0, '#440154'], [0.1111111111111111, '#482878'], - [0.2222222222222222, '#3e4989'], [0.3333333333333333, - '#31688e'], [0.4444444444444444, '#26828e'], - [0.5555555555555556, '#1f9e89'], [0.6666666666666666, - '#35b779'], [0.7777777777777778, '#6ece58'], - [0.8888888888888888, '#b5de2b'], [1.0, '#fde725']], - 'name': 'Sample 7', - 'type': 'histogram2d', - 'x': [], - 'y': []}, - {'colorscale': [[0.0, '#440154'], [0.1111111111111111, '#482878'], - [0.2222222222222222, '#3e4989'], [0.3333333333333333, - '#31688e'], [0.4444444444444444, '#26828e'], - [0.5555555555555556, '#1f9e89'], [0.6666666666666666, - '#35b779'], [0.7777777777777778, '#6ece58'], - [0.8888888888888888, '#b5de2b'], [1.0, '#fde725']], - 'name': 'Sample 6', - 'type': 'histogram2d', - 'x': [], - 'y': []}, - {'colorscale': [[0.0, '#440154'], [0.1111111111111111, '#482878'], - [0.2222222222222222, '#3e4989'], [0.3333333333333333, - '#31688e'], [0.4444444444444444, '#26828e'], - [0.5555555555555556, '#1f9e89'], [0.6666666666666666, - '#35b779'], [0.7777777777777778, '#6ece58'], - [0.8888888888888888, '#b5de2b'], [1.0, '#fde725']], - 'name': 'Sample 7', - 'type': 'histogram2d', - 'x': [], - 'y': []}], - 'layout': {'coloraxis': {'colorbar': {'title': {'text': 'frequency'}}}, - 'template': '...', - 'xaxis': {'title': {'text': 'chunk_sizes'}}, - 'yaxis': {'title': {'text': 'chunk_generation_times'}}} -})",2D histogram of chunk_sizes and chunk_generation_times for japanese|json diff --git a/data/2024-01-22 12:15:16.239311chunk_plots.csv b/data/2024-01-22 12:15:16.239311chunk_plots.csv deleted file mode 100644 index 2a2fe3c8cea35240753e4b8267d05ccc62184edb..0000000000000000000000000000000000000000 --- a/data/2024-01-22 12:15:16.239311chunk_plots.csv +++ /dev/null @@ -1,6168 +0,0 @@ -model,language,template_name,column,path,plot_object,description -gpt-3.5-turbo,japanese,json,chunk_sizes,./html/plots/japanese|json_chunk_sizes.html,"Figure({ - 'data': [{'type': 'scatter', - 'x': [0, 1, 2, ..., 341, 342, 343], - 'y': [1.4, 1.6, 4.0, ..., 1.0, 2.0, 1.0]}], - 'layout': {'template': '...', - 'xaxis': {'title': {'text': 'chunk_index'}}, - 'yaxis': {'title': {'text': 'chunk_sizes'}}} -})",Plot of chunk_sizes for japanese|json -gpt-3.5-turbo,japanese,json,chunk_sizes,./html/plots/japanese|json_chunk_sizes_histogram.html,"Figure({ - 'data': [{'type': 'histogram', - 'x': [2, 1, 7, ..., 2, 1, 4]}], - 'layout': {'template': '...', 'xaxis': {'title': {'text': 'chunk_sizes'}}, 'yaxis': {'title': {'text': 'frequency'}}} -})",Histogram of chunk_sizes for japanese|json -gpt-3.5-turbo,japanese,markdown,chunk_sizes,./html/plots/japanese|markdown_chunk_sizes.html,"Figure({ - 'data': [{'type': 'scatter', - 'x': [0, 1, 2, ..., 768, 769, 770], - 'y': [1.3, 2.6, 1.6, ..., 1.0, 1.0, 4.0]}], - 'layout': {'template': '...', - 'xaxis': {'title': {'text': 'chunk_index'}}, - 'yaxis': {'title': {'text': 'chunk_sizes'}}} -})",Plot of chunk_sizes for japanese|markdown -gpt-3.5-turbo,japanese,markdown,chunk_sizes,./html/plots/japanese|markdown_chunk_sizes_histogram.html,"Figure({ - 'data': [{'type': 'histogram', - 'x': [1, 1, 1, ..., 1, 1, 4]}], - 'layout': {'template': '...', 'xaxis': {'title': {'text': 'chunk_sizes'}}, 'yaxis': {'title': {'text': 'frequency'}}} -})",Histogram of chunk_sizes for japanese|markdown -gpt-3.5-turbo,english,markdown,chunk_sizes,./html/plots/english|markdown_chunk_sizes.html,"Figure({ - 'data': [{'type': 'scatter', - 'x': [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, - 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, - 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, - 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, - 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, - 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, - 98, 99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, - 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 121, 122, - 123, 124, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, - 135, 136, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146, - 147, 148, 149, 150, 151, 152, 153, 154, 155, 156, 157, 158, - 159, 160, 161, 162, 163, 164, 165, 166, 167], - 'y': [2.65, 3.95, 4.9, 5.0, 5.8, 3.3, 4.7, 5.2, 5.85, 5.2, 4.9, 5.4, - 4.8, 4.6, 6.6, 4.75, 7.05, 5.5, 4.05, 3.15, 3.65, 2.75, 4.1, - 4.05, 3.8, 4.15, 3.3, 6.0, 4.6, 3.85, 4.4, 3.55, 3.3, 2.85, - 2.95, 2.7, 1.95, 2.9, 3.45, 3.0, 3.4, 4.25, 3.95, 3.35, 3.7, - 2.1, 3.65, 3.3, 3.35, 2.3, 2.75, 4.35, 2.15, 3.0, 3.05, 3.65, - 4.1, 3.1, 3.0, 3.6, 3.8, 3.55, 2.7, 3.35, 3.0, 4.45, 3.05, - 3.25, 4.6, 3.8, 4.6, 3.9473684210526314, 3.6315789473684212, - 3.0, 3.4210526315789473, 3.5789473684210527, 3.789473684210526, - 3.5789473684210527, 4.526315789473684, 3.1052631578947367, - 4.052631578947368, 3.736842105263158, 3.7777777777777777, - 4.388888888888889, 3.0, 4.166666666666667, 2.7777777777777777, - 2.888888888888889, 2.7777777777777777, 3.411764705882353, - 4.647058823529412, 3.8823529411764706, 4.4, 3.8181818181818183, - 4.090909090909091, 5.2727272727272725, 4.0, 3.5, 4.1, 4.25, - 3.0, 2.5, 1.0, 5.0, 1.0, 3.0, 1.0, 1.0, 1.0, 1.0, 2.0, 2.0, - 1.0, 1.0, 2.0, 1.0, 1.0, 4.0, 9.0, 1.0, 5.0, 4.0, 12.0, 3.0, - 9.0, 3.0, 3.0, 1.0, 1.0, 1.0, 1.0, 2.0, 3.0, 6.0, 1.0, 4.0, - 6.0, 1.0, 3.0, 3.0, 4.0, 3.0, 3.0, 3.0, 5.0, 3.0, 4.0, 5.0, - 6.0, 5.0, 1.0, 2.0, 2.0, 6.0, 9.0, 3.0, 5.0, 4.0, 5.0, 8.0, - 5.0, 4.0, 7.0, 8.0, 6.0, 3.0, 1.0, 4.0]}], - 'layout': {'template': '...', - 'xaxis': {'title': {'text': 'chunk_index'}}, - 'yaxis': {'title': {'text': 'chunk_sizes'}}} -})",Plot of chunk_sizes for english|markdown -gpt-3.5-turbo,english,markdown,chunk_sizes,./html/plots/english|markdown_chunk_sizes_histogram.html,"Figure({ - 'data': [{'type': 'histogram', - 'x': [3, 4, 7, ..., 3, 4, 9]}], - 'layout': {'template': '...', 'xaxis': {'title': {'text': 'chunk_sizes'}}, 'yaxis': {'title': {'text': 'frequency'}}} -})",Histogram of chunk_sizes for english|markdown -gpt-3.5-turbo,english,json,chunk_sizes,./html/plots/english|json_chunk_sizes.html,"Figure({ - 'data': [{'type': 'scatter', - 'x': [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, - 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, - 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, - 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, - 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, - 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93], - 'y': [1.4, 1.65, 2.8, 4.6, 3.55, 2.6, 3.0, 4.65, 4.25, 5.2, 5.1, - 5.75, 5.5, 6.2, 5.8, 4.55, 4.65, 4.9, 5.2, 4.05, 4.85, 2.95, - 3.9, 3.85, 3.5, 3.0, 3.25, 3.0, 3.1, 3.3, 3.6, 3.95, 3.25, 3.3, - 4.15, 4.15, 4.3, 3.85, 4.65, 3.15, 3.35, 2.05, 3.1, 3.05, 4.6, - 2.6, 4.65, 3.4, 4.1, 3.85, 4.3, 3.6, 3.0, 3.4, 3.6, 3.6, 3.45, - 3.0, 3.789473684210526, 1.9473684210526316, 3.1578947368421053, - 2.7777777777777777, 3.7222222222222223, 4.555555555555555, - 3.888888888888889, 4.055555555555555, 3.6470588235294117, - 4.235294117647059, 4.470588235294118, 3.411764705882353, - 3.1176470588235294, 3.8823529411764706, 3.8823529411764706, - 3.75, 4.875, 3.8125, 4.0625, 3.3125, 4.5625, 2.875, 2.8125, - 4.0, 2.75, 3.8333333333333335, 2.909090909090909, - 3.3636363636363638, 2.4545454545454546, 2.272727272727273, - 1.7777777777777777, 3.142857142857143, 3.142857142857143, - 3.4285714285714284, 1.7142857142857142, 4.0]}], - 'layout': {'template': '...', - 'xaxis': {'title': {'text': 'chunk_index'}}, - 'yaxis': {'title': {'text': 'chunk_sizes'}}} -})",Plot of chunk_sizes for english|json -gpt-3.5-turbo,english,json,chunk_sizes,./html/plots/english|json_chunk_sizes_histogram.html,"Figure({ - 'data': [{'type': 'histogram', - 'x': [2, 1, 7, ..., 1, 1, 1]}], - 'layout': {'template': '...', 'xaxis': {'title': {'text': 'chunk_sizes'}}, 'yaxis': {'title': {'text': 'frequency'}}} -})",Histogram of chunk_sizes for english|json -gpt-3.5-turbo,japanese,json,chunk_generation_times,./html/plots/japanese|json_chunk_generation_times.html,"Figure({ - 'data': [{'type': 'scatter', - 'x': [0, 1, 2, ..., 341, 342, 343], - 'y': [0.03325941562652588, 0.022845458984375, 0.008539342880249023, - ..., 0.01340627670288086, 0.0009033679962158203, - 0.0009148120880126953]}], - 'layout': {'template': '...', - 'xaxis': {'title': {'text': 'chunk_index'}}, - 'yaxis': {'title': {'text': 'chunk_generation_times'}}} -})",Plot of chunk_generation_times for japanese|json -gpt-3.5-turbo,japanese,json,chunk_generation_times,./html/plots/japanese|json_chunk_generation_times_histogram.html,"Figure({ - 'data': [{'type': 'histogram', - 'x': [0.055197715759277344, 0.0009396076202392578, - 0.0006830692291259766, ..., 0.09629225730895996, - 0.0002498626708984375, 0.02581787109375]}], - 'layout': {'template': '...', - 'xaxis': {'title': {'text': 'chunk_generation_times'}}, - 'yaxis': {'title': {'text': 'frequency'}}} -})",Histogram of chunk_generation_times for japanese|json -gpt-3.5-turbo,japanese,markdown,chunk_generation_times,./html/plots/japanese|markdown_chunk_generation_times.html,"Figure({ - 'data': [{'type': 'scatter', - 'x': [0, 1, 2, ..., 768, 769, 770], - 'y': [0.10856695175170898, 0.027323269844055177, - 0.0005894899368286133, ..., 0.027635812759399414, - 0.035398006439208984, 0.0004639625549316406]}], - 'layout': {'template': '...', - 'xaxis': {'title': {'text': 'chunk_index'}}, - 'yaxis': {'title': {'text': 'chunk_generation_times'}}} -})",Plot of chunk_generation_times for japanese|markdown -gpt-3.5-turbo,japanese,markdown,chunk_generation_times,./html/plots/japanese|markdown_chunk_generation_times_histogram.html,"Figure({ - 'data': [{'type': 'histogram', - 'x': [0.09664440155029297, 0.0009276866912841797, - 0.0006921291351318359, ..., 0.027635812759399414, - 0.035398006439208984, 0.0004639625549316406]}], - 'layout': {'template': '...', - 'xaxis': {'title': {'text': 'chunk_generation_times'}}, - 'yaxis': {'title': {'text': 'frequency'}}} -})",Histogram of chunk_generation_times for japanese|markdown -gpt-3.5-turbo,english,markdown,chunk_generation_times,./html/plots/english|markdown_chunk_generation_times.html,"Figure({ - 'data': [{'type': 'scatter', - 'x': [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, - 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, - 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, - 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, - 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, - 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, - 98, 99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, - 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 121, 122, - 123, 124, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, - 135, 136, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146, - 147, 148, 149, 150, 151, 152, 153, 154, 155, 156, 157, 158, - 159, 160, 161, 162, 163, 164, 165, 166, 167], - 'y': [0.09208251237869262, 0.026124024391174318, - 0.01616170406341553, 0.02852156162261963, 0.014723885059356689, - 0.020538461208343507, 0.029323899745941163, - 0.016685795783996583, 0.01502150297164917, - 0.032468545436859134, 0.023004639148712158, - 0.018346405029296874, 0.024369895458221436, - 0.02129126787185669, 0.02636735439300537, 0.028070759773254395, - 0.015048229694366455, 0.018386292457580566, - 0.024474453926086426, 0.02241969108581543, 0.02212299108505249, - 0.02697488069534302, 0.018822431564331055, - 0.022496461868286133, 0.02287602424621582, - 0.014856135845184327, 0.018757724761962892, 0.0360129714012146, - 0.02094881534576416, 0.020023763179779053, - 0.023487961292266844, 0.02022104263305664, - 0.021625709533691407, 0.026040089130401612, - 0.01464219093322754, 0.020658397674560548, - 0.022537052631378174, 0.02016826868057251, - 0.023719727993011475, 0.021998834609985352, - 0.014762508869171142, 0.020593512058258056, - 0.031562745571136475, 0.01942124366760254, - 0.018172550201416015, 0.026357293128967285, - 0.014737892150878906, 0.02184560298919678, 0.02521200180053711, - 0.0145959734916687, 0.019272708892822267, 0.02345912456512451, - 0.018707871437072754, 0.02064570188522339, - 0.026726770401000976, 0.014578986167907714, - 0.02704044580459595, 0.0275115966796875, 0.017576706409454346, - 0.02309427261352539, 0.021034085750579835, 0.02014453411102295, - 0.02423384189605713, 0.019620859622955324, - 0.015612244606018066, 0.019633555412292482, - 0.023806488513946532, 0.029540610313415528, - 0.018076753616333006, 0.020523488521575928, - 0.018189358711242675, 0.019011936689677992, - 0.025250146263524106, 0.01884603500366211, - 0.027890945735730623, 0.017041005586322985, - 0.02217518655877364, 0.02624903227153577, 0.017062714225367495, - 0.02720752515290913, 0.035589167946263364, - 0.016492429532502826, 0.022044658660888672, - 0.02782448132832845, 0.018842458724975586, 0.02544562021891276, - 0.023582816123962402, 0.0199509859085083, 0.0204342868593004, - 0.019165529924280503, 0.017221310559441063, - 0.02155288527993595, 0.021391789118448894, - 0.025321657007390804, 0.01995407451282848, - 0.020000804554332386, 0.027066252448342064, - 0.028322601318359376, 0.020383334159851073, - 0.01763775944709778, 0.019829511642456055, - 0.018830597400665283, 0.0003197193145751953, - 0.0002859830856323242, 0.037157535552978516, - 0.0003559589385986328, 0.00033020973205566406, - 0.00030481815338134766, 0.0003345012664794922, - 0.0378338098526001, 0.0003420114517211914, - 0.0004042387008666992, 0.00030684471130371094, - 0.0003019571304321289, 0.03824722766876221, - 0.000339508056640625, 0.0003319978713989258, - 0.00029850006103515625, 0.00029754638671875, - 0.12906873226165771, 0.04114532470703125, - 0.00035190582275390625, 0.04018056392669678, - 0.04078686237335205, 0.0003370046615600586, - 0.040924787521362305, 0.03983438014984131, - 0.0003578662872314453, 0.0003381967544555664, - 0.00032329559326171875, 0.0003101825714111328, - 0.04037809371948242, 0.0003516674041748047, - 0.0003418922424316406, 0.00031316280364990234, - 0.0003008842468261719, 0.03879415988922119, - 0.0003923177719116211, 0.000377655029296875, - 0.0003113746643066406, 0.0003039836883544922, - 0.039052486419677734, 0.00037670135498046875, - 0.0003503561019897461, 0.00037550926208496094, - 0.0003299713134765625, 0.03934800624847412, - 0.0010035037994384766, 0.0003172159194946289, - 0.03936612606048584, 0.04538893699645996, - 0.00036203861236572266, 0.00033092498779296875, - 0.00031876564025878906, 0.035516977310180664, - 0.038269758224487305, 0.00031638145446777344, - 0.0002728700637817383, 0.03825116157531738, - 0.03864848613739014, 0.03890562057495117, 0.04098498821258545, - 0.0005698204040527344, 0.0005306005477905273, - 0.036808133125305176, 0.04005300998687744, 0.0428234338760376, - 0.0005092620849609375]}], - 'layout': {'template': '...', - 'xaxis': {'title': {'text': 'chunk_index'}}, - 'yaxis': {'title': {'text': 'chunk_generation_times'}}} -})",Plot of chunk_generation_times for english|markdown -gpt-3.5-turbo,english,markdown,chunk_generation_times,./html/plots/english|markdown_chunk_generation_times_histogram.html,"Figure({ - 'data': [{'type': 'histogram', - 'x': [0.06274151802062988, 0.0009312629699707031, - 0.0006353855133056641, ..., 0.011092424392700195, - 0.011125326156616211, 0.014921903610229492]}], - 'layout': {'template': '...', - 'xaxis': {'title': {'text': 'chunk_generation_times'}}, - 'yaxis': {'title': {'text': 'frequency'}}} -})",Histogram of chunk_generation_times for english|markdown -gpt-3.5-turbo,english,json,chunk_generation_times,./html/plots/english|json_chunk_generation_times.html,"Figure({ - 'data': [{'type': 'scatter', - 'x': [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, - 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, - 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, - 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, - 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, - 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93], - 'y': [0.10046198368072509, 0.03240053653717041, - 0.024858307838439942, 0.02590036392211914, - 0.015090155601501464, 0.014921844005584717, - 0.041783690452575684, 0.015995442867279053, - 0.020570504665374755, 0.02352551221847534, - 0.014742863178253175, 0.018694496154785155, - 0.02277406454086304, 0.0202506422996521, 0.023777151107788087, - 0.021399533748626708, 0.01908172369003296, 0.01889885663986206, - 0.030153179168701173, 0.0225541353225708, 0.025065648555755615, - 0.017707681655883788, 0.01762690544128418, - 0.024600279331207276, 0.02091813087463379, - 0.020982897281646727, 0.024668455123901367, - 0.01819167137145996, 0.021642518043518067, 0.02440897226333618, - 0.01764235496520996, 0.02233234643936157, 0.019897449016571044, - 0.022547733783721925, 0.01778780221939087, - 0.022352051734924317, 0.0228739857673645, 0.017243289947509767, - 0.024185216426849364, 0.020494675636291503, - 0.017257440090179443, 0.025904011726379395, - 0.018434965610504152, 0.025427448749542236, - 0.026230669021606444, 0.0218292236328125, 0.017258453369140624, - 0.020304083824157715, 0.025457596778869628, - 0.021047306060791016, 0.020934593677520753, - 0.017962396144866943, 0.030893766880035402, - 0.02429497241973877, 0.015818464756011962, 0.02182251214981079, - 0.017441165447235108, 0.02267346382141113, - 0.021955339532149464, 0.02096122189571983, 0.0219482748132003, - 0.027302728758917913, 0.024971723556518555, - 0.01800923877292209, 0.020341939396328397, - 0.021999557813008625, 0.022776225033928368, - 0.026406035703771254, 0.023925683077643898, - 0.018816204632029813, 0.02561175121980555, - 0.017753348631017348, 0.01904933592852424, - 0.031710803508758545, 0.019595131278038025, - 0.01860131323337555, 0.02681751549243927, 0.019831329584121704, - 0.024308815598487854, 0.028108596801757812, - 0.01862257719039917, 0.02156209945678711, 0.018936177094777424, - 0.021108508110046387, 0.020750804380937057, - 0.030380335721102627, 0.020772327076305042, - 0.020700302991000088, 0.026708364486694336, - 0.02281052725655692, 0.02364325523376465, 0.02599930763244629, - 0.025099686213902066, 0.017879009246826172]}], - 'layout': {'template': '...', - 'xaxis': {'title': {'text': 'chunk_index'}}, - 'yaxis': {'title': {'text': 'chunk_generation_times'}}} -})",Plot of chunk_generation_times for english|json -gpt-3.5-turbo,english,json,chunk_generation_times,./html/plots/english|json_chunk_generation_times_histogram.html,"Figure({ - 'data': [{'type': 'histogram', - 'x': [0.06530380249023438, 0.00109100341796875, - 0.0009443759918212891, ..., 0.0182192325592041, - 0.012401819229125977, 0.015912532806396484]}], - 'layout': {'template': '...', - 'xaxis': {'title': {'text': 'chunk_generation_times'}}, - 'yaxis': {'title': {'text': 'frequency'}}} -})",Histogram of chunk_generation_times for english|json -gpt-3.5-turbo,japanese,json,chunk_generation_times_by_chunk_sizes,./html/plots/japanese|json_chunk_generation_times_by_chunk_sizes.html,"Figure({ - 'data': [{'type': 'scatter', - 'x': [0, 1, 2, ..., 341, 342, 343], - 'y': [0.024574017524719237, 0.007615152994791666, - 0.0016790103912353517, ..., 3.455225954350737e-05, - 2.31632819542518e-06, 2.339672859367507e-06]}], - 'layout': {'template': '...', - 'xaxis': {'title': {'text': 'chunk_index'}}, - 'yaxis': {'title': {'text': 'chunk_generation_times_by_chunk_sizes'}}} -})",Plot of chunk_generation_times_by_chunk_sizes for japanese|json -gpt-3.5-turbo,japanese,json,chunk_generation_times_by_chunk_sizes,./html/plots/japanese|json_chunk_generation_times_by_chunk_sizes_histogram.html,"Figure({ - 'data': [{'type': 'histogram', - 'x': [0.027598857879638672, 0.0003132025400797526, - 6.830692291259766e-05, ..., 0.00011829515639921371, - 3.0657996429256133e-07, 3.152365212912088e-05]}], - 'layout': {'template': '...', - 'xaxis': {'title': {'text': 'chunk_generation_times_by_chunk_sizes'}}, - 'yaxis': {'title': {'text': 'frequency'}}} -})",Histogram of chunk_generation_times_by_chunk_sizes for japanese|json -gpt-3.5-turbo,japanese,markdown,chunk_generation_times_by_chunk_sizes,./html/plots/japanese|markdown_chunk_generation_times_by_chunk_sizes.html,"Figure({ - 'data': [{'type': 'scatter', - 'x': [0, 1, 2, ..., 768, 769, 770], - 'y': [0.10252033472061158, 0.005723926850727626, - 0.00015428165594736734, ..., 3.4893702979039664e-05, - 4.463809134830893e-05, 5.821362044311677e-07]}], - 'layout': {'template': '...', - 'xaxis': {'title': {'text': 'chunk_index'}}, - 'yaxis': {'title': {'text': 'chunk_generation_times_by_chunk_sizes'}}} -})",Plot of chunk_generation_times_by_chunk_sizes for japanese|markdown -gpt-3.5-turbo,japanese,markdown,chunk_generation_times_by_chunk_sizes,./html/plots/japanese|markdown_chunk_generation_times_by_chunk_sizes_histogram.html,"Figure({ - 'data': [{'type': 'histogram', - 'x': [0.09664440155029297, 0.00046384334564208984, - 0.00023070971171061197, ..., 3.4893702979039664e-05, - 4.463809134830893e-05, 5.821362044311677e-07]}], - 'layout': {'template': '...', - 'xaxis': {'title': {'text': 'chunk_generation_times_by_chunk_sizes'}}, - 'yaxis': {'title': {'text': 'frequency'}}} -})",Histogram of chunk_generation_times_by_chunk_sizes for japanese|markdown -gpt-3.5-turbo,english,markdown,chunk_generation_times_by_chunk_sizes,./html/plots/english|markdown_chunk_generation_times_by_chunk_sizes.html,"Figure({ - 'data': [{'type': 'scatter', - 'x': [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, - 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, - 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, - 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, - 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, - 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, - 98, 99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, - 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 121, 122, - 123, 124, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, - 135, 136, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146, - 147, 148, 149, 150, 151, 152, 153, 154, 155, 156, 157, 158, - 159, 160, 161, 162, 163, 164, 165, 166, 167], - 'y': [0.03632562756538391, 0.0041558427611986795, - 0.0015482904225544842, 0.001825864957524585, - 0.0008218889501803647, 0.000929749278026769, - 0.0010206748414825178, 0.0005587356991541535, - 0.0004158333411608837, 0.0007294862860957942, - 0.0005001733624220186, 0.00034631598065473036, - 0.00040755672467626827, 0.0003383196497622263, - 0.0003800022888386437, 0.00035712016487067196, - 0.00019103740172862242, 0.000218210582249543, - 0.00026796686353620686, 0.00023573625600167053, - 0.0002323285202751794, 0.00026580079774429386, - 0.00017241300318212942, 0.00021267361273871947, - 0.0002016752708531258, 0.0001309303547095743, - 0.00015869303614781739, 0.00026248786388367363, - 0.00016811253463466544, 0.00015285407199782197, - 0.00016983772856239, 0.00014906236564247413, - 0.00014580468267572224, 0.0001798519244119315, - 0.00010193680908334596, 0.00013948870924051696, - 0.00014732003932834737, 0.00012420512763942562, - 0.00015552588294370082, 0.00013642120079356855, - 9.279294113447869e-05, 0.00012410135881899386, - 0.00017717047952708328, 0.00011449380917642991, - 0.00010220058833488828, 0.0001417657532181025, - 8.147143102416876e-05, 0.00011272820802376782, - 0.00013282181558725903, 7.679730910306085e-05, - 9.789502667772756e-05, 0.00011335508502119439, - 8.829357089929674e-05, 0.00010367267611149014, - 0.00012067089010691825, 7.01513324933404e-05, - 0.00012273148858170195, 0.00011814963883815212, - 8.107124991382932e-05, 0.00010006237447860349, - 9.044187934664484e-05, 8.961044588314943e-05, - 9.811671195620328e-05, 8.126747041158346e-05, - 6.573715673389812e-05, 7.863378246974325e-05, - 9.551787039155241e-05, 0.00011430785201089551, - 7.016163336196306e-05, 8.012737695460754e-05, - 6.826918517944221e-05, 7.0438192818372e-05, - 8.969769308821329e-05, 6.837849595508661e-05, - 9.846763872844533e-05, 6.10720910246614e-05, - 7.478768011964158e-05, 8.663701706745981e-05, - 5.81746144180273e-05, 8.932049205458166e-05, - 0.00011453196496396676, 5.5263752787186024e-05, - 6.936049506852808e-05, 8.769330826921082e-05, - 5.9844635253995374e-05, 8.124097379450256e-05, - 7.445598390489517e-05, 6.141147240032585e-05, - 6.16378090714557e-05, 5.856617861823866e-05, - 5.3039432746347645e-05, 6.564544623331413e-05, - 6.453609817836689e-05, 6.968950336014621e-05, - 5.723248678470528e-05, 5.6514190443413204e-05, - 7.545989961151253e-05, 7.464698045814285e-05, - 5.593965934784983e-05, 4.937732527848694e-05, - 4.375327639145874e-05, 5.000265807728637e-05, - 7.011388477526213e-07, 6.203537649291198e-07, - 8.042756613198813e-05, 7.655030937605007e-07, - 7.08604575226747e-07, 6.527155318658408e-07, - 7.147462958963508e-07, 8.066910416332644e-05, - 7.261389633146315e-07, 8.546272745596178e-07, - 6.473517116112046e-07, 6.356992219623766e-07, - 8.018286723010945e-05, 7.102679009218097e-07, - 6.931062033380497e-07, 6.180125487270315e-07, - 6.047690786966463e-07, 0.00026180270235630365, - 8.262113394986195e-05, 7.01007615047622e-07, - 7.817230335933225e-05, 7.889141658288599e-05, - 6.406932729278681e-07, 7.736254729936163e-05, - 7.487665441699494e-05, 6.714189253873271e-07, - 6.333272555347685e-07, 6.042908285265771e-07, - 5.786988272595762e-07, 7.505221880944688e-05, - 6.500321703785669e-07, 6.250315218128713e-07, - 5.714649701640554e-07, 5.450801572937897e-07, - 6.952358403086235e-05, 7.018207010941344e-07, - 6.719840378947953e-07, 5.511056005427268e-07, - 5.342419830483167e-07, 6.827357765677925e-05, - 6.551327912703805e-07, 6.061524255877961e-07, - 6.440982196997616e-07, 5.630909786289463e-07, - 6.669153601436292e-05, 1.6865610074596244e-06, - 5.278135099744242e-07, 6.496060406020766e-05, - 7.477584348675447e-05, 5.944804800750783e-07, - 5.416120913141878e-07, 5.166379906949579e-07, - 5.6736385479521825e-05, 6.084222293241225e-05, - 4.990243761321347e-07, 4.276960247362669e-07, - 5.948858720889173e-05, 5.936787425098331e-05, - 5.9307348437425566e-05, 6.209846698876584e-05, - 8.543034543519255e-07, 7.860748856155961e-07, - 5.405012206359057e-05, 5.855703214455766e-05, - 6.251596186282861e-05, 7.391321987822025e-07]}], - 'layout': {'template': '...', - 'xaxis': {'title': {'text': 'chunk_index'}}, - 'yaxis': {'title': {'text': 'chunk_generation_times_by_chunk_sizes'}}} -})",Plot of chunk_generation_times_by_chunk_sizes for english|markdown -gpt-3.5-turbo,english,markdown,chunk_generation_times_by_chunk_sizes,./html/plots/english|markdown_chunk_generation_times_by_chunk_sizes_histogram.html,"Figure({ - 'data': [{'type': 'histogram', - 'x': [0.02091383934020996, 0.00013303756713867188, - 4.538467952183315e-05, ..., 3.7348230278451834e-05, - 3.696121646716349e-05, 4.813517293622417e-05]}], - 'layout': {'template': '...', - 'xaxis': {'title': {'text': 'chunk_generation_times_by_chunk_sizes'}}, - 'yaxis': {'title': {'text': 'frequency'}}} -})",Histogram of chunk_generation_times_by_chunk_sizes for english|markdown -gpt-3.5-turbo,english,json,chunk_generation_times_by_chunk_sizes,./html/plots/english|json_chunk_generation_times_by_chunk_sizes.html,"Figure({ - 'data': [{'type': 'scatter', - 'x': [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, - 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, - 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, - 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, - 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, - 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93], - 'y': [0.08881364862124125, 0.012830307015350886, - 0.0064611540332673075, 0.0030427001522044944, - 0.0012172913284965487, 0.0010328626803360436, - 0.002154427544347976, 0.0008185346057660483, - 0.0008266825447255308, 0.000760871848028172, - 0.00045842723370057606, 0.00046171496183959924, - 0.00047127716587811477, 0.00038408483282244944, - 0.0003980975856065783, 0.0003487464370932618, - 0.0002965170545073433, 0.0002700690074389441, - 0.00037837427634977207, 0.0002866590783409241, - 0.00029493569297919835, 0.00020610502551212962, - 0.0002056610358036507, 0.0002556709545080788, - 0.00021863463385897843, 0.0002219719517650634, - 0.00024266534764616813, 0.00017596374882596956, - 0.00020285578972633502, 0.00021708531685676584, - 0.0001548711550720346, 0.00018800492851703547, - 0.00015937359887022992, 0.00017812613615565616, - 0.0001415090139225613, 0.00016561077338479954, - 0.00016583709916750757, 0.00012602757341873813, - 0.00016227505976302718, 0.00013630295275824343, - 0.00011568545287166481, 0.000161301372429186, - 0.00011680775120967695, 0.00015618929982248828, - 0.0001531285078796367, 0.00013086565473866444, - 0.0001005047225825474, 0.00011247224608928101, - 0.0001386543480009729, 0.00011219802282768186, - 0.0001064520749112099, 9.064017950346037e-05, - 0.00015197036174066016, 0.00011933885090705775, - 7.726775757721345e-05, 0.00010199303274006767, - 8.038324391604707e-05, 0.00010754656963653864, - 9.890817006997501e-05, 9.641565009028522e-05, - 9.889980322311977e-05, 0.00011965482689836298, - 0.00011026073189590966, 7.68795829726359e-05, - 8.488755457789014e-05, 9.2034010611518e-05, - 9.30288186306384e-05, 0.00010473556974214237, - 9.396757780640082e-05, 7.280453944623646e-05, - 9.839988391097912e-05, 6.629642442848702e-05, - 7.012915942254425e-05, 0.00011638762448193335, - 7.01056800013593e-05, 6.539925829258799e-05, - 9.312883553243395e-05, 6.794533329217034e-05, - 8.297807489765248e-05, 9.471462087460092e-05, - 6.133946290140733e-05, 7.026849327649994e-05, - 5.961504138096624e-05, 6.563258693968294e-05, - 6.383154896123252e-05, 9.528001542696267e-05, - 6.246172585711863e-05, 6.181504461999184e-05, - 7.949675912702044e-05, 6.619173043054431e-05, - 6.797917138507241e-05, 7.434168847616238e-05, - 7.122499242952558e-05, 5.27404402561244e-05]}], - 'layout': {'template': '...', - 'xaxis': {'title': {'text': 'chunk_index'}}, - 'yaxis': {'title': {'text': 'chunk_generation_times_by_chunk_sizes'}}} -})",Plot of chunk_generation_times_by_chunk_sizes for english|json -gpt-3.5-turbo,english,json,chunk_generation_times_by_chunk_sizes,./html/plots/english|json_chunk_generation_times_by_chunk_sizes_histogram.html,"Figure({ - 'data': [{'type': 'histogram', - 'x': [0.03265190124511719, 0.0003636678059895833, - 9.443759918212891e-05, ..., 5.2354116549437074e-05, - 3.553529865079076e-05, 4.5464379446847095e-05]}], - 'layout': {'template': '...', - 'xaxis': {'title': {'text': 'chunk_generation_times_by_chunk_sizes'}}, - 'yaxis': {'title': {'text': 'frequency'}}} -})",Histogram of chunk_generation_times_by_chunk_sizes for english|json -gpt-3.5-turbo,japanese,json,"chunk_sizes, chunk_generation_times",./html/plots/japanese|json_scatter.html,"Figure({ - 'data': [{'mode': 'markers', - 'name': 'Sample 6', - 'type': 'scatter', - 'x': [2, 1, 7, ..., 1, 2, 1], - 'y': [0.055197715759277344, 0.0009396076202392578, - 0.0006830692291259766, ..., 0.0014231204986572266, - 0.001180410385131836, 0.0013620853424072266]}, - {'mode': 'markers', - 'name': 'Sample 7', - 'type': 'scatter', - 'x': [2, 1, 7, 2, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 1, 1, 1, - 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, - 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, - 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, - 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, - 1, 1, 2, 1, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 2, 1, - 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, - 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, - 1, 1, 1, 2, 1], - 'y': [0.06697797775268555, 0.0014584064483642578, - 0.0009691715240478516, 0.05404186248779297, - 0.0013899803161621094, 0.0010700225830078125, - 0.14432930946350098, 0.0012371540069580078, - 0.0010542869567871094, 0.08168625831604004, - 0.0014157295227050781, 0.001219034194946289, - 0.07998824119567871, 0.001378774642944336, - 0.0009958744049072266, 0.10132598876953125, - 0.0012145042419433594, 0.0010390281677246094, - 0.10170602798461914, 0.0012950897216796875, - 0.0011432170867919922, 0.056665897369384766, - 0.0013267993927001953, 0.0011022090911865234, - 0.11384272575378418, 0.0038230419158935547, - 0.0013895034790039062, 0.09027528762817383, - 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{'mode': 'markers', 'name': 'Sample 7', 'type': 'scatter', 'x': [], 'y': []}, - {'mode': 'markers', 'name': 'Sample 6', 'type': 'scatter', 'x': [], 'y': []}, - {'mode': 'markers', 'name': 'Sample 7', 'type': 'scatter', 'x': [], 'y': []}, - {'mode': 'markers', 'name': 'Sample 6', 'type': 'scatter', 'x': [], 'y': []}, - {'mode': 'markers', 'name': 'Sample 7', 'type': 'scatter', 'x': [], 'y': []}], - 'layout': {'template': '...', - 'xaxis': {'title': {'text': 'chunk_sizes'}}, - 'yaxis': {'title': {'text': 'chunk_generation_times'}}} -})",Scatter plot of chunk_sizes and chunk_generation_times for japanese|json -gpt-3.5-turbo,japanese,json,"chunk_sizes, chunk_generation_times",./html/plots/japanese|json_hist2d.html,"Figure({ - 'data': [{'colorscale': [[0.0, '#440154'], [0.1111111111111111, '#482878'], - [0.2222222222222222, '#3e4989'], [0.3333333333333333, - '#31688e'], [0.4444444444444444, '#26828e'], - [0.5555555555555556, '#1f9e89'], [0.6666666666666666, - '#35b779'], [0.7777777777777778, '#6ece58'], - 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[0.2222222222222222, '#3e4989'], [0.3333333333333333, - '#31688e'], [0.4444444444444444, '#26828e'], - [0.5555555555555556, '#1f9e89'], [0.6666666666666666, - '#35b779'], [0.7777777777777778, '#6ece58'], - [0.8888888888888888, '#b5de2b'], [1.0, '#fde725']], - 'name': 'Sample 7', - 'type': 'histogram2d', - 'x': [], - 'y': []}, - {'colorscale': [[0.0, '#440154'], [0.1111111111111111, '#482878'], - [0.2222222222222222, '#3e4989'], [0.3333333333333333, - '#31688e'], [0.4444444444444444, '#26828e'], - [0.5555555555555556, '#1f9e89'], [0.6666666666666666, - '#35b779'], [0.7777777777777778, '#6ece58'], - [0.8888888888888888, '#b5de2b'], [1.0, '#fde725']], - 'name': 'Sample 6', - 'type': 'histogram2d', - 'x': [], - 'y': []}, - {'colorscale': [[0.0, '#440154'], [0.1111111111111111, '#482878'], - [0.2222222222222222, '#3e4989'], [0.3333333333333333, - '#31688e'], [0.4444444444444444, '#26828e'], - [0.5555555555555556, '#1f9e89'], [0.6666666666666666, - '#35b779'], [0.7777777777777778, '#6ece58'], - [0.8888888888888888, '#b5de2b'], [1.0, '#fde725']], - 'name': 'Sample 7', - 'type': 'histogram2d', - 'x': [], - 'y': []}, - {'colorscale': [[0.0, '#440154'], [0.1111111111111111, '#482878'], - [0.2222222222222222, '#3e4989'], [0.3333333333333333, - '#31688e'], [0.4444444444444444, '#26828e'], - [0.5555555555555556, '#1f9e89'], [0.6666666666666666, - '#35b779'], [0.7777777777777778, '#6ece58'], - [0.8888888888888888, '#b5de2b'], [1.0, '#fde725']], - 'name': 'Sample 6', - 'type': 'histogram2d', - 'x': [], - 'y': []}, - {'colorscale': [[0.0, '#440154'], [0.1111111111111111, '#482878'], - [0.2222222222222222, '#3e4989'], [0.3333333333333333, - '#31688e'], [0.4444444444444444, '#26828e'], - [0.5555555555555556, '#1f9e89'], [0.6666666666666666, - '#35b779'], [0.7777777777777778, '#6ece58'], - [0.8888888888888888, '#b5de2b'], [1.0, '#fde725']], - 'name': 'Sample 7', - 'type': 'histogram2d', - 'x': [], - 'y': []}], - 'layout': {'coloraxis': {'colorbar': {'title': {'text': 'frequency'}}}, - 'template': '...', - 'xaxis': {'title': {'text': 'chunk_sizes'}}, - 'yaxis': {'title': {'text': 'chunk_generation_times'}}} -})",2D histogram of chunk_sizes and chunk_generation_times for japanese|json -gpt-3.5-turbo,japanese,markdown,"chunk_sizes, chunk_generation_times",./html/plots/japanese|markdown_scatter.html,"Figure({ - 'data': [{'mode': 'markers', - 'name': 'Sample 2', - 'type': 'scatter', - 'x': [1, 1, 1, ..., 1, 1, 1], - 'y': [0.09664440155029297, 0.0009276866912841797, - 0.0006921291351318359, ..., 0.01478886604309082, - 0.0007951259613037109, 0.0006318092346191406]}, - {'mode': 'markers', - 'name': 'Sample 3', - 'type': 'scatter', - 'x': [1, 1, 1, ..., 1, 3, 1], - 'y': [0.11492753028869629, 0.0013332366943359375, - 0.0011086463928222656, ..., 0.0007293224334716797, - 0.0006046295166015625, 0.0009331703186035156]}, - {'mode': 'markers', 'name': 'Sample 2', 'type': 'scatter', 'x': [], 'y': []}, - {'mode': 'markers', 'name': 'Sample 3', 'type': 'scatter', 'x': [], 'y': []}, - {'mode': 'markers', 'name': 'Sample 2', 'type': 'scatter', 'x': [], 'y': []}, - {'mode': 'markers', 'name': 'Sample 3', 'type': 'scatter', 'x': [], 'y': []}, - {'mode': 'markers', - 'name': 'Sample 2', - 'type': 'scatter', - 'x': [1, 3, 4, ..., 3, 1, 4], - 'y': [0.03938937187194824, 0.03878307342529297, 0.0003204345703125, - ..., 0.00020241737365722656, 0.04965066909790039, - 0.0004153251647949219]}, - {'mode': 'markers', - 'name': 'Sample 3', - 'type': 'scatter', - 'x': [2, 5, 1, ..., 9, 1, 4], - 'y': [0.03808403015136719, 0.03988242149353027, - 0.000316619873046875, ..., 0.04375195503234863, - 0.00030517578125, 0.0002968311309814453]}, - {'mode': 'markers', - 'name': 'Sample 2', - 'type': 'scatter', - 'x': [1, 1, 1, ..., 1, 3, 1], - 'y': [0.0943903923034668, 0.0007405281066894531, - 0.0007641315460205078, ..., 0.0010237693786621094, - 0.001007080078125, 0.0010919570922851562]}, - {'mode': 'markers', - 'name': 'Sample 3', - 'type': 'scatter', - 'x': [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, - 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, - 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, - 1, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, - 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 1, - 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 1, 1, - 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, - 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 1], - 'y': [0.0979311466217041, 0.00096893310546875, - 0.0010690689086914062, 0.07782816886901855, - 0.0010001659393310547, 0.0009646415710449219, - 0.051312923431396484, 0.0009915828704833984, - 0.0009713172912597656, 0.0912940502166748, - 0.0010423660278320312, 0.001104116439819336, - 0.07774829864501953, 0.0010311603546142578, - 0.000997304916381836, 0.11951732635498047, - 0.0010483264923095703, 0.0009708404541015625, - 0.05830645561218262, 0.0009930133819580078, - 0.0009558200836181641, 0.05755949020385742, - 0.0010159015655517578, 0.001651763916015625, - 0.09955286979675293, 0.0010182857513427734, - 0.0009832382202148438, 0.09042596817016602, - 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0.0010330677032470703, 0.04735088348388672, - 0.0010559558868408203, 0.0010323524475097656, - 0.0010175704956054688, 0.0010192394256591797]}, - {'mode': 'markers', - 'name': 'Sample 2', - 'type': 'scatter', - 'x': [1, 3, 4, ..., 3, 1, 4], - 'y': [0.4988229274749756, 0.041541337966918945, - 0.00046896934509277344, ..., 0.0002532005310058594, - 0.04337000846862793, 0.0003113746643066406]}, - {'mode': 'markers', - 'name': 'Sample 3', - 'type': 'scatter', - 'x': [2, 5, 1, ..., 9, 1, 4], - 'y': [0.053075551986694336, 0.023623943328857422, - 0.00044035911560058594, ..., 0.04376816749572754, - 0.00023746490478515625, 0.0002741813659667969]}, - {'mode': 'markers', - 'name': 'Sample 2', - 'type': 'scatter', - 'x': [1, 1, 1, ..., 1, 2, 4], - 'y': [0.022631406784057617, 0.022909164428710938, - 0.0002346038818359375, ..., 0.00040221214294433594, - 0.0003783702850341797, 0.030768871307373047]}, - {'mode': 'markers', - 'name': 'Sample 3', - 'type': 'scatter', - 'x': [2, 5, 1, ..., 1, 1, 4], - 'y': [0.02977275848388672, 0.10252237319946289, - 0.0004799365997314453, ..., 0.027635812759399414, - 0.035398006439208984, 0.0004639625549316406]}, - {'mode': 'markers', 'name': 'Sample 2', 'type': 'scatter', 'x': [], 'y': []}, - {'mode': 'markers', 'name': 'Sample 3', 'type': 'scatter', 'x': [], 'y': []}, - {'mode': 'markers', 'name': 'Sample 2', 'type': 'scatter', 'x': [], 'y': []}, - {'mode': 'markers', 'name': 'Sample 3', 'type': 'scatter', 'x': [], 'y': []}, - {'mode': 'markers', 'name': 'Sample 2', 'type': 'scatter', 'x': [], 'y': []}, - {'mode': 'markers', 'name': 'Sample 3', 'type': 'scatter', 'x': [], 'y': []}], - 'layout': {'template': '...', - 'xaxis': {'title': {'text': 'chunk_sizes'}}, - 'yaxis': {'title': {'text': 'chunk_generation_times'}}} -})",Scatter plot of chunk_sizes and chunk_generation_times for japanese|markdown -gpt-3.5-turbo,japanese,markdown,"chunk_sizes, chunk_generation_times",./html/plots/japanese|markdown_hist2d.html,"Figure({ - 'data': [{'colorscale': [[0.0, '#440154'], [0.1111111111111111, '#482878'], - [0.2222222222222222, '#3e4989'], [0.3333333333333333, - '#31688e'], [0.4444444444444444, '#26828e'], - [0.5555555555555556, '#1f9e89'], [0.6666666666666666, - '#35b779'], [0.7777777777777778, '#6ece58'], - [0.8888888888888888, '#b5de2b'], [1.0, '#fde725']], - 'name': 'Sample 2', - 'type': 'histogram2d', - 'x': [1, 1, 1, ..., 1, 1, 1], - 'y': [0.09664440155029297, 0.0009276866912841797, - 0.0006921291351318359, ..., 0.01478886604309082, - 0.0007951259613037109, 0.0006318092346191406]}, - {'colorscale': [[0.0, '#440154'], [0.1111111111111111, '#482878'], - [0.2222222222222222, '#3e4989'], [0.3333333333333333, - '#31688e'], [0.4444444444444444, '#26828e'], - [0.5555555555555556, '#1f9e89'], [0.6666666666666666, - '#35b779'], [0.7777777777777778, '#6ece58'], - [0.8888888888888888, '#b5de2b'], [1.0, '#fde725']], - 'name': 'Sample 3', - 'type': 'histogram2d', - 'x': [1, 1, 1, ..., 1, 3, 1], - 'y': [0.11492753028869629, 0.0013332366943359375, - 0.0011086463928222656, ..., 0.0007293224334716797, - 0.0006046295166015625, 0.0009331703186035156]}, - {'colorscale': [[0.0, '#440154'], [0.1111111111111111, '#482878'], - [0.2222222222222222, '#3e4989'], [0.3333333333333333, - '#31688e'], [0.4444444444444444, '#26828e'], - [0.5555555555555556, '#1f9e89'], [0.6666666666666666, - '#35b779'], [0.7777777777777778, '#6ece58'], - [0.8888888888888888, '#b5de2b'], [1.0, '#fde725']], - 'name': 'Sample 2', - 'type': 'histogram2d', - 'x': [], - 'y': []}, - {'colorscale': [[0.0, '#440154'], [0.1111111111111111, '#482878'], - [0.2222222222222222, '#3e4989'], [0.3333333333333333, - '#31688e'], [0.4444444444444444, '#26828e'], - [0.5555555555555556, '#1f9e89'], [0.6666666666666666, - '#35b779'], [0.7777777777777778, '#6ece58'], - [0.8888888888888888, '#b5de2b'], [1.0, '#fde725']], - 'name': 'Sample 3', - 'type': 'histogram2d', - 'x': [], - 'y': []}, - {'colorscale': [[0.0, '#440154'], [0.1111111111111111, '#482878'], - [0.2222222222222222, '#3e4989'], [0.3333333333333333, - '#31688e'], [0.4444444444444444, '#26828e'], - 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'x': [1, 3, 4, ..., 3, 1, 4], - 'y': [0.03938937187194824, 0.03878307342529297, 0.0003204345703125, - ..., 0.00020241737365722656, 0.04965066909790039, - 0.0004153251647949219]}, - {'colorscale': [[0.0, '#440154'], [0.1111111111111111, '#482878'], - [0.2222222222222222, '#3e4989'], [0.3333333333333333, - '#31688e'], [0.4444444444444444, '#26828e'], - [0.5555555555555556, '#1f9e89'], [0.6666666666666666, - '#35b779'], [0.7777777777777778, '#6ece58'], - [0.8888888888888888, '#b5de2b'], [1.0, '#fde725']], - 'name': 'Sample 3', - 'type': 'histogram2d', - 'x': [2, 5, 1, ..., 9, 1, 4], - 'y': [0.03808403015136719, 0.03988242149353027, - 0.000316619873046875, ..., 0.04375195503234863, - 0.00030517578125, 0.0002968311309814453]}, - {'colorscale': [[0.0, '#440154'], [0.1111111111111111, '#482878'], - [0.2222222222222222, '#3e4989'], [0.3333333333333333, - '#31688e'], [0.4444444444444444, '#26828e'], - [0.5555555555555556, '#1f9e89'], [0.6666666666666666, - '#35b779'], [0.7777777777777778, '#6ece58'], - 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[0.8888888888888888, '#b5de2b'], [1.0, '#fde725']], - 'name': 'Sample 2', - 'type': 'histogram2d', - 'x': [], - 'y': []}, - {'colorscale': [[0.0, '#440154'], [0.1111111111111111, '#482878'], - [0.2222222222222222, '#3e4989'], [0.3333333333333333, - '#31688e'], [0.4444444444444444, '#26828e'], - [0.5555555555555556, '#1f9e89'], [0.6666666666666666, - '#35b779'], [0.7777777777777778, '#6ece58'], - [0.8888888888888888, '#b5de2b'], [1.0, '#fde725']], - 'name': 'Sample 3', - 'type': 'histogram2d', - 'x': [], - 'y': []}], - 'layout': {'coloraxis': {'colorbar': {'title': {'text': 'frequency'}}}, - 'template': '...', - 'xaxis': {'title': {'text': 'chunk_sizes'}}, - 'yaxis': {'title': {'text': 'chunk_generation_times'}}} -})",2D histogram of chunk_sizes and chunk_generation_times for japanese|markdown -gpt-3.5-turbo,english,markdown,"chunk_sizes, chunk_generation_times",./html/plots/english|markdown_scatter.html,"Figure({ - 'data': [{'mode': 'markers', - 'name': 'Sample 0', - 'type': 'scatter', - 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Execution time (s)=%{y}', @@ -26,7 +26,7 @@ path,plot_object,description,comment,plot_json 'type': 'bar', 'x': array(['Mixtral-8x7B-Instruct-v0.1'], dtype=object), 'xaxis': 'x', - 'y': array([8.43355885]), + 'y': array([7.14219763]), 'yaxis': 'y'}, {'alignmentgroup': 'True', 'hovertemplate': 'Model=%{x}
Execution time (s)=%{y}', @@ -40,143 +40,136 @@ path,plot_object,description,comment,plot_json 'type': 'bar', 'x': array(['TinyLlama/TinyLlama-1.1B-Chat-v1.0'], dtype=object), 'xaxis': 'x', - 'y': array([1.44886649]), + 'y': array([1.29026454]), 'yaxis': 'y'}, {'alignmentgroup': 'True', 'hovertemplate': 'Model=%{x}
Execution time (s)=%{y}', - 'legendgroup': 'gemini-pro', + 'legendgroup': 'chat-bison', 'marker': {'color': '#ab63fa', 'pattern': {'shape': ''}}, - 'name': 'gemini-pro', - 'offsetgroup': 'gemini-pro', + 'name': 'chat-bison', + 'offsetgroup': 'chat-bison', 'orientation': 'v', 'showlegend': True, 'textposition': 'auto', 'type': 'bar', - 'x': array(['gemini-pro'], dtype=object), + 'x': array(['chat-bison'], dtype=object), 'xaxis': 'x', - 'y': array([nan]), + 'y': array([3.89024363]), 'yaxis': 'y'}, {'alignmentgroup': 'True', 'hovertemplate': 'Model=%{x}
Execution time (s)=%{y}', - 'legendgroup': 'gpt-3.5-turbo', + 'legendgroup': 'chat-bison-32k', 'marker': {'color': '#FFA15A', 'pattern': {'shape': ''}}, - 'name': 'gpt-3.5-turbo', - 'offsetgroup': 'gpt-3.5-turbo', + 'name': 'chat-bison-32k', + 'offsetgroup': 'chat-bison-32k', 'orientation': 'v', 'showlegend': True, 'textposition': 'auto', 'type': 'bar', - 'x': array(['gpt-3.5-turbo'], dtype=object), + 'x': array(['chat-bison-32k'], dtype=object), 'xaxis': 'x', - 'y': array([5.12583753]), + 'y': array([4.12817777]), 'yaxis': 'y'}, {'alignmentgroup': 'True', 'hovertemplate': 'Model=%{x}
Execution time (s)=%{y}', - 'legendgroup': 'llama-2-70b-chat', + 'legendgroup': 'gemini-pro', 'marker': {'color': '#19d3f3', 'pattern': {'shape': ''}}, - 'name': 'llama-2-70b-chat', - 'offsetgroup': 'llama-2-70b-chat', + 'name': 'gemini-pro', + 'offsetgroup': 'gemini-pro', 'orientation': 'v', 'showlegend': True, 'textposition': 'auto', 'type': 'bar', - 'x': array(['llama-2-70b-chat'], dtype=object), + 'x': array(['gemini-pro'], dtype=object), 'xaxis': 'x', - 'y': array([5.16784139]), + 'y': array([4.72138064]), 'yaxis': 'y'}, {'alignmentgroup': 'True', 'hovertemplate': 'Model=%{x}
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Execution cost ($)=%{y}', @@ -190,7 +183,7 @@ path,plot_object,description,comment,plot_json 'type': 'bar', 'x': array(['gpt-3.5-turbo', 'gpt-3.5-turbo'], dtype=object), 'xaxis': 'x', - 'y': array([0.002944, 0.002944]), + 'y': array([0.144438, 0.144438]), 'yaxis': 'y'}, {'alignmentgroup': 'True', 'hovertemplate': 'Model=%{x}
Execution cost ($)=%{y}', @@ -204,7 +197,7 @@ path,plot_object,description,comment,plot_json 'type': 'bar', 'x': array(['gpt-4-turbo'], dtype=object), 'xaxis': 'x', - 'y': array([0.]), + 'y': array([0.44014]), 'yaxis': 'y'}, {'alignmentgroup': 'True', 'hovertemplate': 'Model=%{x}
Execution cost ($)=%{y}', @@ -218,7 +211,7 @@ path,plot_object,description,comment,plot_json 'type': 'bar', 'x': array(['gpt-4'], dtype=object), 'xaxis': 'x', - 'y': array([0.]), + 'y': array([1.1724]), 'yaxis': 'y'}, {'alignmentgroup': 'True', 'hovertemplate': 'Model=%{x}
Execution cost ($)=%{y}', @@ -232,7 +225,7 @@ path,plot_object,description,comment,plot_json 'type': 'bar', 'x': array(['llama-2-70b-chat'], dtype=object), 'xaxis': 'x', - 'y': array([0.00078]), + 'y': array([0.0186864]), 'yaxis': 'y'}, {'alignmentgroup': 'True', 'hovertemplate': 'Model=%{x}
Execution cost ($)=%{y}', @@ -246,7 +239,7 @@ path,plot_object,description,comment,plot_json 'type': 'bar', 'x': array(['Mixtral-8x7B-Instruct-v0.1'], dtype=object), 'xaxis': 'x', - 'y': array([0.0010602]), + 'y': array([0.0781551]), 'yaxis': 'y'}, {'alignmentgroup': 'True', 'hovertemplate': 'Model=%{x}
Execution cost ($)=%{y}', @@ -302,7 +295,7 @@ path,plot_object,description,comment,plot_json 'type': 'bar', 'x': array(['gemini-pro'], dtype=object), 'xaxis': 'x', - 'y': array([0.000205]), + 'y': array([0.022971]), 'yaxis': 'y'}, {'alignmentgroup': 'True', 'hovertemplate': 'Model=%{x}
Execution cost ($)=%{y}', @@ -316,7 +309,7 @@ path,plot_object,description,comment,plot_json 'type': 'bar', 'x': array(['chat-bison'], dtype=object), 'xaxis': 'x', - 'y': array([0.]), + 'y': array([0.008985]), 'yaxis': 'y'}, {'alignmentgroup': 'True', 'hovertemplate': 'Model=%{x}
Execution cost ($)=%{y}', @@ -330,12 +323,76 @@ path,plot_object,description,comment,plot_json 'type': 'bar', 'x': array(['chat-bison-32k'], dtype=object), 'xaxis': 'x', - 'y': array([0.]), + 'y': array([0.0089655]), 'yaxis': 'y'}], 'layout': {'barmode': 'relative', 'legend': {'title': {'text': 'Model'}, 'tracegroupgap': 0}, 'template': '...', - 'title': {'text': 'Costs of execution of 12 test queries per model'}, + 'title': {'text': 'Costs of execution of 80 test queries per model'}, 'xaxis': {'anchor': 'y', 'domain': [0.0, 1.0], 'title': {'text': 'Model'}}, 'yaxis': {'anchor': 'x', 'domain': [0.0, 1.0], 'title': {'text': 'Execution cost ($)'}}} -})",Costs of execution of 12 test queries per model,Note that some providers bill by token count and some by execution time. In the second case we used averaged pausing and resuming time to calculate the cost and assumed that all queries have been done in one session. 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+gemini-pro,morning,4.72138064004937,425.09166666666664,49.891666666666666 +gpt-3.5-turbo,afternoon,4.666725277900696,302.1666666666667,32.0 +gpt-3.5-turbo,evening,4.351089119911194,305.25,28.5 +gpt-3.5-turbo,morning,5.336839800789242,479.2785714285714,53.92142857142857 +gpt-4,morning,15.5218456586202,389.1875,44.125 +gpt-4-turbo,morning,14.008529031276703,433.075,49.975 +llama-2-70b-chat,afternoon,2.1692867279052734,292.0,43.5 +llama-2-70b-chat,evening,5.552149415016174,967.5,141.25 +llama-2-70b-chat,morning,6.175082007679371,662.7416666666667,94.30833333333334 +zephyr-7b-beta,afternoon,,, +zephyr-7b-beta,evening,,, +zephyr-7b-beta,morning,3.2387993240356447,112.57,17.26 diff --git a/data/2024-01-25 13:34:46.224347_summary.csv b/data/2024-01-25 13:34:46.224347_summary.csv new file mode 100644 index 0000000000000000000000000000000000000000..966af163377ac48d3ba7593c0014923c6622c2e8 --- /dev/null +++ b/data/2024-01-25 13:34:46.224347_summary.csv @@ -0,0 +1,59 @@ 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+zephyr-7b-beta,japanese,json,1.921021181344986,29.75,3.3,1.1829025844930416,1.0,7.0,0.042037644869764565,0.018090486526489258,0.4599947929382324 +zephyr-7b-beta,japanese,markdown,1.8884475827217102,26.6,1.75,1.0350194552529184,1.0,4.0,0.04097196471366437,0.02583909034729004,0.4606599807739258 diff --git a/data/2024-01-26 11:01:41.169428_general_plot.csv b/data/2024-01-26 11:01:41.169428_general_plot.csv new file mode 100644 index 0000000000000000000000000000000000000000..e10cfe99565cc77f44f07b41d4cf941f8e1981d6 --- /dev/null +++ b/data/2024-01-26 11:01:41.169428_general_plot.csv @@ -0,0 +1,398 @@ +path,plot_object,description,comment,plot_json +./html/plots/response_times.html,"Figure({ + 'data': [{'alignmentgroup': 'True', + 'hovertemplate': 'Model=%{x}
Execution time (s)=%{y}', + 'legendgroup': 'Mistral-7B-Instruct-v0.2', + 'marker': {'color': '#636efa', 'pattern': {'shape': ''}}, + 'name': 'Mistral-7B-Instruct-v0.2', + 'offsetgroup': 'Mistral-7B-Instruct-v0.2', + 'orientation': 'v', + 'showlegend': True, + 'textposition': 'auto', + 'type': 'bar', + 'x': array(['Mistral-7B-Instruct-v0.2'], dtype=object), + 'xaxis': 'x', + 'y': array([3.17454003]), + 'yaxis': 'y'}, + {'alignmentgroup': 'True', + 'hovertemplate': 'Model=%{x}
Execution time (s)=%{y}', + 'legendgroup': 'Mixtral-8x7B-Instruct-v0.1', + 'marker': {'color': '#EF553B', 'pattern': {'shape': ''}}, + 'name': 'Mixtral-8x7B-Instruct-v0.1', + 'offsetgroup': 'Mixtral-8x7B-Instruct-v0.1', + 'orientation': 'v', + 'showlegend': True, + 'textposition': 'auto', + 'type': 'bar', + 'x': array(['Mixtral-8x7B-Instruct-v0.1'], dtype=object), + 'xaxis': 'x', + 'y': array([7.14219763]), + 'yaxis': 'y'}, + {'alignmentgroup': 'True', + 'hovertemplate': 'Model=%{x}
Execution time (s)=%{y}', + 'legendgroup': 'TinyLlama/TinyLlama-1.1B-Chat-v1.0', + 'marker': {'color': '#00cc96', 'pattern': {'shape': ''}}, + 'name': 'TinyLlama/TinyLlama-1.1B-Chat-v1.0', + 'offsetgroup': 'TinyLlama/TinyLlama-1.1B-Chat-v1.0', + 'orientation': 'v', + 'showlegend': True, + 'textposition': 'auto', + 'type': 'bar', + 'x': array(['TinyLlama/TinyLlama-1.1B-Chat-v1.0'], dtype=object), + 'xaxis': 'x', + 'y': array([1.29026454]), + 'yaxis': 'y'}, + {'alignmentgroup': 'True', + 'hovertemplate': 'Model=%{x}
Execution time (s)=%{y}', + 'legendgroup': 'chat-bison', + 'marker': {'color': '#ab63fa', 'pattern': {'shape': ''}}, + 'name': 'chat-bison', + 'offsetgroup': 'chat-bison', + 'orientation': 'v', + 'showlegend': True, + 'textposition': 'auto', + 'type': 'bar', + 'x': array(['chat-bison'], dtype=object), + 'xaxis': 'x', + 'y': array([3.89024363]), + 'yaxis': 'y'}, + {'alignmentgroup': 'True', + 'hovertemplate': 'Model=%{x}
Execution time (s)=%{y}', + 'legendgroup': 'chat-bison-32k', + 'marker': {'color': '#FFA15A', 'pattern': {'shape': ''}}, + 'name': 'chat-bison-32k', + 'offsetgroup': 'chat-bison-32k', + 'orientation': 'v', + 'showlegend': True, + 'textposition': 'auto', + 'type': 'bar', + 'x': array(['chat-bison-32k'], dtype=object), + 'xaxis': 'x', + 'y': array([4.12817777]), + 'yaxis': 'y'}, + {'alignmentgroup': 'True', + 'hovertemplate': 'Model=%{x}
Execution time (s)=%{y}', + 'legendgroup': 'gemini-pro', + 'marker': {'color': '#19d3f3', 'pattern': {'shape': ''}}, + 'name': 'gemini-pro', + 'offsetgroup': 'gemini-pro', + 'orientation': 'v', + 'showlegend': True, + 'textposition': 'auto', + 'type': 'bar', + 'x': array(['gemini-pro'], dtype=object), + 'xaxis': 'x', + 'y': array([4.72138064]), + 'yaxis': 'y'}, + {'alignmentgroup': 'True', + 'hovertemplate': 'Model=%{x}
Execution time (s)=%{y}', + 'legendgroup': 'gpt-3.5-turbo', + 'marker': {'color': '#FF6692', 'pattern': {'shape': ''}}, + 'name': 'gpt-3.5-turbo', + 'offsetgroup': 'gpt-3.5-turbo', + 'orientation': 'v', + 'showlegend': True, + 'textposition': 'auto', + 'type': 'bar', + 'x': array(['gpt-3.5-turbo'], dtype=object), + 'xaxis': 'x', + 'y': array([5.28237349]), + 'yaxis': 'y'}, + {'alignmentgroup': 'True', + 'hovertemplate': 'Model=%{x}
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size (B params)""}},""legend"":{""title"":{""text"":""Model""},""tracegroupgap"":0},""title"":{""text"":""Model sizes in billions of parameters""},""barmode"":""relative""}}" diff --git a/data/2024-01-26 16:13:38.191636_model_costs.csv b/data/2024-01-26 16:13:38.191636_model_costs.csv new file mode 100644 index 0000000000000000000000000000000000000000..acbb815c04fa0279a295e934f8580e084981020c --- /dev/null +++ b/data/2024-01-26 16:13:38.191636_model_costs.csv @@ -0,0 +1,13 @@ +model,provider,provider_pricing,cost_per_token +gpt-3.5-turbo,OpenAI,"$1 / 1M input tokens, $2 / 1M output tokens","$1 / 1M input tokens, $2 / 1M output tokens" +gpt-4-turbo,OpenAI,"$10 / 1M input tokens, $30 / 1M output tokens","$10 / 1M input tokens, $30 / 1M output tokens" +gpt-4,OpenAI,"$30 / 1M input tokens, $60 / 1M output tokens","$30 / 1M input tokens, $60 / 1M output tokens" +gpt-3.5-turbo,OpenAI,"$1 / 1M input tokens, $2 / 1M output tokens","$1 / 1M input tokens, $2 / 1M output tokens" +llama-2-70b-chat,Together AI,$0.2 / 1M tokens,$0.2 / 1M tokens +Mixtral-8x7B-Instruct-v0.1,Together AI,$0.9 / 1M tokens,$0.9 / 1M tokens +zephyr-7b-beta,Hugging Face Inference Endpoint,$1.3 / hour,$5.364983589763427e-11 / 1M tokens +Mistral-7B-Instruct-v0.2,Hugging Face Inference Endpoint,$1.3 / hour,$5.2585398066299045e-11 / 1M tokens +TinyLlama/TinyLlama-1.1B-Chat-v1.0,Hugging Face Inference Endpoint,$0.6 / hour,$1.0752204477787017e-11 / 1M tokens +gemini-pro,Google VertexAI,"$0.25 / 1M input characters, $0.5 / 1M output characters (60 queries per minute are free)","$0.25 / 1M input tokens, $0.5 / 1M output tokens" +chat-bison (PaLM 2),Google VertexAI,"$0.25 / 1M input tokens, $0.5 / 1M output tokens","$0.25 / 1M input tokens, $0.5 / 1M output tokens" +chat-bison-32k (PaLM 2 32K),Google VertexAI,"$0.25 / 1M input tokens, $0.5 / 1M output tokens","$0.25 / 1M input tokens, $0.5 / 1M output tokens" diff --git a/data/2024-01-26 16:16:56.390177_model_costs.csv b/data/2024-01-26 16:16:56.390177_model_costs.csv new file mode 100644 index 0000000000000000000000000000000000000000..174f890f3a52d1068b0c592d83546b2efce2ac7d --- /dev/null +++ b/data/2024-01-26 16:16:56.390177_model_costs.csv @@ -0,0 +1,13 @@ +model,provider,provider_pricing,cost_per_token +gpt-3.5-turbo,OpenAI,"$1.00 / 1M input tokens, $2.00 / 1M output tokens","$1.00 / 1M input tokens, $2.00 / 1M output tokens" +gpt-4-turbo,OpenAI,"$10.00 / 1M input tokens, $30.00 / 1M output tokens","$10.00 / 1M input tokens, $30.00 / 1M output tokens" +gpt-4,OpenAI,"$30.00 / 1M input tokens, $60.00 / 1M output tokens","$30.00 / 1M input tokens, $60.00 / 1M output tokens" +gpt-3.5-turbo,OpenAI,"$1.00 / 1M input tokens, $2.00 / 1M output tokens","$1.00 / 1M input tokens, $2.00 / 1M output tokens" +llama-2-70b-chat,Together AI,$0.20 / 1M tokens,$0.20 / 1M tokens +Mixtral-8x7B-Instruct-v0.1,Together AI,$0.90 / 1M tokens,$0.90 / 1M tokens +zephyr-7b-beta,Hugging Face Inference Endpoint,$1.30 / hour,$0.00 / 1M tokens +Mistral-7B-Instruct-v0.2,Hugging Face Inference Endpoint,$1.30 / hour,$0.00 / 1M tokens +TinyLlama/TinyLlama-1.1B-Chat-v1.0,Hugging Face Inference Endpoint,$0.60 / hour,$0.00 / 1M tokens +gemini-pro,Google VertexAI,"$0.25 / 1M input characters, $0.5 / 1M output characters (60 queries per minute are free)","$0.25 / 1M input tokens, $0.50 / 1M output tokens" +chat-bison (PaLM 2),Google VertexAI,"$0.25 / 1M input tokens, $0.50 / 1M output tokens","$0.25 / 1M input tokens, $0.50 / 1M output tokens" +chat-bison-32k (PaLM 2 32K),Google VertexAI,"$0.25 / 1M input tokens, $0.50 / 1M output tokens","$0.25 / 1M input tokens, $0.50 / 1M output tokens" diff --git a/data/2024-01-26 16:19:55.237955_model_costs.csv b/data/2024-01-26 16:19:55.237955_model_costs.csv new file mode 100644 index 0000000000000000000000000000000000000000..ad2263be490d44415c5a4403c5a07854341c4aa3 --- /dev/null +++ b/data/2024-01-26 16:19:55.237955_model_costs.csv @@ -0,0 +1,13 @@ +model,provider,provider_pricing,cost_per_token +gpt-3.5-turbo,OpenAI,"$1 / 1M input tokens, $2 / 1M output tokens","$1 / 1M input tokens, $2 / 1M output tokens" +gpt-4-turbo,OpenAI,"$10 / 1M input tokens, $30 / 1M output tokens","$10 / 1M input tokens, $30 / 1M output tokens" +gpt-4,OpenAI,"$30 / 1M input tokens, $60 / 1M output tokens","$30 / 1M input tokens, $60 / 1M output tokens" +gpt-3.5-turbo,OpenAI,"$1 / 1M input tokens, $2 / 1M output tokens","$1 / 1M input tokens, $2 / 1M output tokens" +llama-2-70b-chat,Together AI,$0.2 / 1M tokens,$0.2 / 1M tokens +Mixtral-8x7B-Instruct-v0.1,Together AI,$0.9 / 1M tokens,$0.9 / 1M tokens +zephyr-7b-beta,Hugging Face Inference Endpoint,$1.3 / hour,$5.4e-11 / 1M tokens +Mistral-7B-Instruct-v0.2,Hugging Face Inference Endpoint,$1.3 / hour,$5.3e-11 / 1M tokens +TinyLlama/TinyLlama-1.1B-Chat-v1.0,Hugging Face Inference Endpoint,$0.6 / hour,$1.1e-11 / 1M tokens +gemini-pro,Google VertexAI,"$0.25 / 1M input characters, $0.5 / 1M output characters (60 queries per minute are free)","$0.25 / 1M input tokens, $0.5 / 1M output tokens" +chat-bison (PaLM 2),Google VertexAI,"$0.25 / 1M input tokens, $0.5 / 1M output tokens","$0.25 / 1M input tokens, $0.5 / 1M output tokens" +chat-bison-32k (PaLM 2 32K),Google VertexAI,"$0.25 / 1M input tokens, $0.5 / 1M output tokens","$0.25 / 1M input tokens, $0.5 / 1M output tokens" diff --git a/data/2024-01-26 16:21:10.212177_model_costs.csv b/data/2024-01-26 16:21:10.212177_model_costs.csv new file mode 100644 index 0000000000000000000000000000000000000000..68ca2c6b1b9bdcf9676ec28ab41a714d9f28a19e --- /dev/null +++ b/data/2024-01-26 16:21:10.212177_model_costs.csv @@ -0,0 +1,13 @@ +model,provider,provider_pricing,cost_per_token +gpt-3.5-turbo,OpenAI,"$1 / 1M input tokens, $2 / 1M output tokens","$1 / 1M input tokens, $2 / 1M output tokens" +gpt-4-turbo,OpenAI,"$10 / 1M input tokens, $30 / 1M output tokens","$10 / 1M input tokens, $30 / 1M output tokens" +gpt-4,OpenAI,"$30 / 1M input tokens, $60 / 1M output tokens","$30 / 1M input tokens, $60 / 1M output tokens" +gpt-3.5-turbo,OpenAI,"$1 / 1M input tokens, $2 / 1M output tokens","$1 / 1M input tokens, $2 / 1M output tokens" +llama-2-70b-chat,Together AI,$0.2 / 1M tokens,$0.2 / 1M tokens +Mixtral-8x7B-Instruct-v0.1,Together AI,$0.9 / 1M tokens,$0.9 / 1M tokens +zephyr-7b-beta,Hugging Face Inference Endpoint,$1.3 / hour,$54 / 1M tokens +Mistral-7B-Instruct-v0.2,Hugging Face Inference Endpoint,$1.3 / hour,$53 / 1M tokens +TinyLlama/TinyLlama-1.1B-Chat-v1.0,Hugging Face Inference Endpoint,$0.6 / hour,$11 / 1M tokens +gemini-pro,Google VertexAI,"$0.25 / 1M input characters, $0.5 / 1M output characters (60 queries per minute are free)","$0.25 / 1M input tokens, $0.5 / 1M output tokens" +chat-bison (PaLM 2),Google VertexAI,"$0.25 / 1M input tokens, $0.5 / 1M output tokens","$0.25 / 1M input tokens, $0.5 / 1M output tokens" +chat-bison-32k (PaLM 2 32K),Google VertexAI,"$0.25 / 1M input tokens, $0.5 / 1M output tokens","$0.25 / 1M input tokens, $0.5 / 1M output tokens" diff --git a/data/2024-01-26 16:21:34.661653_model_costs.csv b/data/2024-01-26 16:21:34.661653_model_costs.csv new file mode 100644 index 0000000000000000000000000000000000000000..68ca2c6b1b9bdcf9676ec28ab41a714d9f28a19e --- /dev/null +++ b/data/2024-01-26 16:21:34.661653_model_costs.csv @@ -0,0 +1,13 @@ +model,provider,provider_pricing,cost_per_token +gpt-3.5-turbo,OpenAI,"$1 / 1M input tokens, $2 / 1M output tokens","$1 / 1M input tokens, $2 / 1M output tokens" +gpt-4-turbo,OpenAI,"$10 / 1M input tokens, $30 / 1M output tokens","$10 / 1M input tokens, $30 / 1M output tokens" +gpt-4,OpenAI,"$30 / 1M input tokens, $60 / 1M output tokens","$30 / 1M input tokens, $60 / 1M output tokens" +gpt-3.5-turbo,OpenAI,"$1 / 1M input tokens, $2 / 1M output tokens","$1 / 1M input tokens, $2 / 1M output tokens" +llama-2-70b-chat,Together AI,$0.2 / 1M tokens,$0.2 / 1M tokens +Mixtral-8x7B-Instruct-v0.1,Together AI,$0.9 / 1M tokens,$0.9 / 1M tokens +zephyr-7b-beta,Hugging Face Inference Endpoint,$1.3 / hour,$54 / 1M tokens +Mistral-7B-Instruct-v0.2,Hugging Face Inference Endpoint,$1.3 / hour,$53 / 1M tokens +TinyLlama/TinyLlama-1.1B-Chat-v1.0,Hugging Face Inference Endpoint,$0.6 / hour,$11 / 1M tokens +gemini-pro,Google VertexAI,"$0.25 / 1M input characters, $0.5 / 1M output characters (60 queries per minute are free)","$0.25 / 1M input tokens, $0.5 / 1M output tokens" +chat-bison (PaLM 2),Google VertexAI,"$0.25 / 1M input tokens, $0.5 / 1M output tokens","$0.25 / 1M input tokens, $0.5 / 1M output tokens" +chat-bison-32k (PaLM 2 32K),Google VertexAI,"$0.25 / 1M input tokens, $0.5 / 1M output tokens","$0.25 / 1M input tokens, $0.5 / 1M output tokens" diff --git a/data/2024-01-26 16:25:47.914140_model_costs.csv b/data/2024-01-26 16:25:47.914140_model_costs.csv new file mode 100644 index 0000000000000000000000000000000000000000..68152bf3e7fbe3e5c6dbf06360e1b90465dff4d7 --- /dev/null +++ b/data/2024-01-26 16:25:47.914140_model_costs.csv @@ -0,0 +1,13 @@ +model,provider,provider_pricing,cost_per_token +gpt-3.5-turbo,OpenAI,"$1 / 1M input tokens, $2 / 1M output tokens","$1 / 1M input tokens, $2 / 1M output tokens" +gpt-4-turbo,OpenAI,"$10 / 1M input tokens, $30 / 1M output tokens","$10 / 1M input tokens, $30 / 1M output tokens" +gpt-4,OpenAI,"$30 / 1M input tokens, $60 / 1M output tokens","$30 / 1M input tokens, $60 / 1M output tokens" +gpt-3.5-turbo,OpenAI,"$1 / 1M input tokens, $2 / 1M output tokens","$1 / 1M input tokens, $2 / 1M output tokens" +llama-2-70b-chat,Together AI,$0.2 / 1M tokens,$0.2 / 1M tokens +Mixtral-8x7B-Instruct-v0.1,Together AI,$0.9 / 1M tokens,$0.9 / 1M tokens +zephyr-7b-beta,Hugging Face Inference Endpoint,$1.3 / hour,$0.14 / 1M tokens +Mistral-7B-Instruct-v0.2,Hugging Face Inference Endpoint,$1.3 / hour,$0.14 / 1M tokens +TinyLlama/TinyLlama-1.1B-Chat-v1.0,Hugging Face Inference Endpoint,$0.6 / hour,$0.026 / 1M tokens +gemini-pro,Google VertexAI,"$0.25 / 1M input characters, $0.5 / 1M output characters (60 queries per minute are free)","$0.25 / 1M input tokens, $0.5 / 1M output tokens" +chat-bison (PaLM 2),Google VertexAI,"$0.25 / 1M input tokens, $0.5 / 1M output tokens","$0.25 / 1M input tokens, $0.5 / 1M output tokens" +chat-bison-32k (PaLM 2 32K),Google VertexAI,"$0.25 / 1M input tokens, $0.5 / 1M output tokens","$0.25 / 1M input tokens, $0.5 / 1M output tokens" diff --git a/data/2024-01-26 16:32:54.481637_model_costs.csv b/data/2024-01-26 16:32:54.481637_model_costs.csv new file mode 100644 index 0000000000000000000000000000000000000000..7e2c9e476be046d9a62433ff1031e9c88857562e --- /dev/null +++ b/data/2024-01-26 16:32:54.481637_model_costs.csv @@ -0,0 +1,13 @@ +model,provider,cost_per_token,provider_pricing +gpt-3.5-turbo,OpenAI,"$1 / 1M input tokens, $2 / 1M output tokens","$1 / 1M input tokens, $2 / 1M output tokens" +gpt-4-turbo,OpenAI,"$10 / 1M input tokens, $30 / 1M output tokens","$10 / 1M input tokens, $30 / 1M output tokens" +gpt-4,OpenAI,"$30 / 1M input tokens, $60 / 1M output tokens","$30 / 1M input tokens, $60 / 1M output tokens" +gpt-3.5-turbo,OpenAI,"$1 / 1M input tokens, $2 / 1M output tokens","$1 / 1M input tokens, $2 / 1M output tokens" +llama-2-70b-chat,Together AI,$0.2 / 1M tokens,$0.2 / 1M tokens +Mixtral-8x7B-Instruct-v0.1,Together AI,$0.9 / 1M tokens,$0.9 / 1M tokens +zephyr-7b-beta,Hugging Face Inference Endpoint,$0.14 / 1M tokens,$1.3 / hour +Mistral-7B-Instruct-v0.2,Hugging Face Inference Endpoint,$0.14 / 1M tokens,$1.3 / hour +TinyLlama/TinyLlama-1.1B-Chat-v1.0,Hugging Face Inference Endpoint,$0.026 / 1M tokens,$0.6 / hour +gemini-pro,Google VertexAI,"$0.25 / 1M input tokens, $0.5 / 1M output tokens","$0.25 / 1M input characters, $0.5 / 1M output characters (60 queries per minute are free)" +chat-bison (PaLM 2),Google VertexAI,"$0.25 / 1M input tokens, $0.5 / 1M output tokens","$0.25 / 1M input tokens, $0.5 / 1M output tokens" +chat-bison-32k (PaLM 2 32K),Google VertexAI,"$0.25 / 1M input tokens, $0.5 / 1M output tokens","$0.25 / 1M input tokens, $0.5 / 1M output tokens" diff --git a/data/2024-01-26 16:43:36.843194_general_plot.csv b/data/2024-01-26 16:43:36.843194_general_plot.csv new file mode 100644 index 0000000000000000000000000000000000000000..da0af585035d80288d2a20a1b50cdd82d6371cf9 --- /dev/null +++ b/data/2024-01-26 16:43:36.843194_general_plot.csv @@ -0,0 +1,398 @@ +path,plot_object,description,comment,plot_json +./html/plots/response_times.html,"Figure({ + 'data': [{'alignmentgroup': 'True', + 'hovertemplate': 'Model=%{x}
Execution time (s)=%{y}', + 'legendgroup': 'Mistral-7B-Instruct-v0.2', + 'marker': {'color': '#636efa', 'pattern': {'shape': ''}}, + 'name': 'Mistral-7B-Instruct-v0.2', + 'offsetgroup': 'Mistral-7B-Instruct-v0.2', + 'orientation': 'v', + 'showlegend': True, + 'textposition': 'auto', + 'type': 'bar', + 'x': array(['Mistral-7B-Instruct-v0.2'], dtype=object), + 'xaxis': 'x', + 'y': array([3.17454003]), + 'yaxis': 'y'}, + {'alignmentgroup': 'True', + 'hovertemplate': 'Model=%{x}
Execution time (s)=%{y}', + 'legendgroup': 'Mixtral-8x7B-Instruct-v0.1', + 'marker': {'color': '#EF553B', 'pattern': {'shape': ''}}, + 'name': 'Mixtral-8x7B-Instruct-v0.1', + 'offsetgroup': 'Mixtral-8x7B-Instruct-v0.1', + 'orientation': 'v', + 'showlegend': True, + 'textposition': 'auto', + 'type': 'bar', + 'x': array(['Mixtral-8x7B-Instruct-v0.1'], dtype=object), + 'xaxis': 'x', + 'y': array([7.14219763]), + 'yaxis': 'y'}, + {'alignmentgroup': 'True', + 'hovertemplate': 'Model=%{x}
Execution time (s)=%{y}', + 'legendgroup': 'TinyLlama/TinyLlama-1.1B-Chat-v1.0', + 'marker': {'color': '#00cc96', 'pattern': {'shape': ''}}, + 'name': 'TinyLlama/TinyLlama-1.1B-Chat-v1.0', + 'offsetgroup': 'TinyLlama/TinyLlama-1.1B-Chat-v1.0', + 'orientation': 'v', + 'showlegend': True, + 'textposition': 'auto', + 'type': 'bar', + 'x': array(['TinyLlama/TinyLlama-1.1B-Chat-v1.0'], dtype=object), + 'xaxis': 'x', + 'y': array([1.29026454]), + 'yaxis': 'y'}, + {'alignmentgroup': 'True', + 'hovertemplate': 'Model=%{x}
Execution time (s)=%{y}', + 'legendgroup': 'chat-bison', + 'marker': {'color': '#ab63fa', 'pattern': {'shape': ''}}, + 'name': 'chat-bison', + 'offsetgroup': 'chat-bison', + 'orientation': 'v', + 'showlegend': True, + 'textposition': 'auto', + 'type': 'bar', + 'x': array(['chat-bison'], dtype=object), + 'xaxis': 'x', + 'y': array([3.89024363]), + 'yaxis': 'y'}, + {'alignmentgroup': 'True', + 'hovertemplate': 'Model=%{x}
Execution time (s)=%{y}', + 'legendgroup': 'chat-bison-32k', + 'marker': {'color': '#FFA15A', 'pattern': {'shape': ''}}, + 'name': 'chat-bison-32k', + 'offsetgroup': 'chat-bison-32k', + 'orientation': 'v', + 'showlegend': True, + 'textposition': 'auto', + 'type': 'bar', + 'x': array(['chat-bison-32k'], dtype=object), + 'xaxis': 'x', + 'y': array([4.12817777]), + 'yaxis': 'y'}, + {'alignmentgroup': 'True', + 'hovertemplate': 'Model=%{x}
Execution time (s)=%{y}', + 'legendgroup': 'gemini-pro', + 'marker': {'color': '#19d3f3', 'pattern': {'shape': ''}}, + 'name': 'gemini-pro', + 'offsetgroup': 'gemini-pro', + 'orientation': 'v', + 'showlegend': True, + 'textposition': 'auto', + 'type': 'bar', + 'x': array(['gemini-pro'], dtype=object), + 'xaxis': 'x', + 'y': array([4.72138064]), + 'yaxis': 'y'}, + {'alignmentgroup': 'True', + 'hovertemplate': 'Model=%{x}
Execution time (s)=%{y}', + 'legendgroup': 'gpt-3.5-turbo', + 'marker': {'color': '#FF6692', 'pattern': {'shape': ''}}, + 'name': 'gpt-3.5-turbo', + 'offsetgroup': 'gpt-3.5-turbo', + 'orientation': 'v', + 'showlegend': True, + 'textposition': 'auto', + 'type': 'bar', + 'x': array(['gpt-3.5-turbo'], dtype=object), + 'xaxis': 'x', + 'y': array([5.28237349]), + 'yaxis': 'y'}, + {'alignmentgroup': 'True', + 'hovertemplate': 'Model=%{x}
Execution time (s)=%{y}', + 'legendgroup': 'gpt-4', + 'marker': {'color': '#B6E880', 'pattern': {'shape': ''}}, + 'name': 'gpt-4', + 'offsetgroup': 'gpt-4', + 'orientation': 'v', + 'showlegend': True, + 'textposition': 'auto', + 'type': 'bar', + 'x': array(['gpt-4'], dtype=object), + 'xaxis': 'x', + 'y': array([15.52184566]), + 'yaxis': 'y'}, + {'alignmentgroup': 'True', + 'hovertemplate': 'Model=%{x}
Execution time (s)=%{y}', + 'legendgroup': 'gpt-4-turbo', + 'marker': {'color': '#FF97FF', 'pattern': {'shape': ''}}, + 'name': 'gpt-4-turbo', + 'offsetgroup': 'gpt-4-turbo', + 'orientation': 'v', + 'showlegend': True, + 'textposition': 'auto', + 'type': 'bar', + 'x': array(['gpt-4-turbo'], dtype=object), + 'xaxis': 'x', + 'y': array([14.00852903]), + 'yaxis': 'y'}, + {'alignmentgroup': 'True', + 'hovertemplate': 'Model=%{x}
Execution time (s)=%{y}', + 'legendgroup': 'llama-2-70b-chat', + 'marker': {'color': '#FECB52', 'pattern': {'shape': ''}}, + 'name': 'llama-2-70b-chat', + 'offsetgroup': 'llama-2-70b-chat', + 'orientation': 'v', + 'showlegend': True, + 'textposition': 'auto', + 'type': 'bar', + 'x': array(['llama-2-70b-chat'], dtype=object), + 'xaxis': 'x', + 'y': array([6.0658799]), + 'yaxis': 'y'}, + {'alignmentgroup': 'True', + 'hovertemplate': 'Model=%{x}
Execution time (s)=%{y}', + 'legendgroup': 'zephyr-7b-beta', + 'marker': {'color': '#636efa', 'pattern': {'shape': ''}}, + 'name': 'zephyr-7b-beta', + 'offsetgroup': 'zephyr-7b-beta', + 'orientation': 'v', + 'showlegend': True, + 'textposition': 'auto', + 'type': 'bar', + 'x': array(['zephyr-7b-beta'], dtype=object), + 'xaxis': 'x', + 'y': array([3.23879932]), + 'yaxis': 'y'}], + 'layout': {'barmode': 'relative', + 'legend': {'title': {'text': 'Model'}, 'tracegroupgap': 0}, + 'template': '...', + 'title': {'text': 'Model endpoints response times'}, + 'xaxis': {'anchor': 'y', + 'categoryarray': [Mistral-7B-Instruct-v0.2, + Mixtral-8x7B-Instruct-v0.1, + TinyLlama/TinyLlama-1.1B-Chat-v1.0, + chat-bison, chat-bison-32k, gemini-pro, + gpt-3.5-turbo, gpt-4, gpt-4-turbo, + llama-2-70b-chat, zephyr-7b-beta], + 'categoryorder': 'array', + 'domain': [0.0, 1.0], + 'title': {'text': 'Model'}}, + 'yaxis': {'anchor': 'x', 'domain': [0.0, 1.0], 'title': {'text': 'Execution time (s)'}}} +})",Model endpoints response times,,"{""data"":[{""alignmentgroup"":""True"",""hovertemplate"":""Model=%{x}\u003cbr\u003eExecution time (s)=%{y}\u003cextra\u003e\u003c\u002fextra\u003e"",""legendgroup"":""Mistral-7B-Instruct-v0.2"",""marker"":{""color"":""#636efa"",""pattern"":{""shape"":""""}},""name"":""Mistral-7B-Instruct-v0.2"",""offsetgroup"":""Mistral-7B-Instruct-v0.2"",""orientation"":""v"",""showlegend"":true,""textposition"":""auto"",""x"":[""Mistral-7B-Instruct-v0.2""],""xaxis"":""x"",""y"":[3.174540030956268],""yaxis"":""y"",""type"":""bar""},{""alignmentgroup"":""True"",""hovertemplate"":""Model=%{x}\u003cbr\u003eExecution time 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+Mistral-7B-Instruct-v0.2,evening,3.2679351409276327,216.63333333333333,31.5 +Mistral-7B-Instruct-v0.2,morning,3.174540030956268,113.0,16.27 +Mixtral-8x7B-Instruct-v0.1,afternoon,7.426922065019608,450.4875,51.85 +Mixtral-8x7B-Instruct-v0.1,evening,4.979682341865871,457.8,53.708333333333336 +Mixtral-8x7B-Instruct-v0.1,morning,7.142197625471814,494.9583333333333,57.74166666666667 +TinyLlama/TinyLlama-1.1B-Chat-v1.0,afternoon,1.538642168045044,169.46666666666667,26.083333333333332 +TinyLlama/TinyLlama-1.1B-Chat-v1.0,evening,1.7001954774061838,222.51666666666668,35.575 +TinyLlama/TinyLlama-1.1B-Chat-v1.0,morning,1.2902645373344421,106.18,16.74 +chat-bison,morning,3.890243631601334,398.075,49.0 +chat-bison (PaLM 2),afternoon,3.866238150000572,381.7875,40.3875 +chat-bison (PaLM 2),evening,2.8466253956158956,358.525,39.25833333333333 +chat-bison-32k,morning,4.128177767992019,389.925,48.025 +chat-bison-32k (PaLM 2 32K),afternoon,4.844334444403648,371.25,38.7375 +chat-bison-32k (PaLM 2 32K),evening,3.981116022666295,348.93333333333334,36.525 +gemini-pro,afternoon,3.6972034962972007,352.2,33.9375 +gemini-pro,evening,3.810917937329837,335.68333333333334,36.21666666666667 +gemini-pro,morning,4.72138064004937,425.09166666666664,49.891666666666666 +gpt-3.5-turbo,afternoon,4.228875203738137,364.92857142857144,36.42857142857143 +gpt-3.5-turbo,evening,3.9572247514184915,375.75,37.660377358490564 +gpt-3.5-turbo,morning,5.336839800789242,479.2785714285714,53.92142857142857 +gpt-4,afternoon,20.52127287968868,307.175,31.975 +gpt-4,evening,16.028902428833085,306.075,31.925 +gpt-4,morning,15.5218456586202,389.1875,44.125 +gpt-4-turbo,afternoon,23.51892908215523,396.40833333333336,41.858333333333334 +gpt-4-turbo,evening,15.113789739608764,455.105,39.97 +gpt-4-turbo,morning,14.008529031276703,433.075,49.975 +llama-2-70b-chat,afternoon,4.851686128755895,671.2317073170732,83.5609756097561 +llama-2-70b-chat,evening,4.701648034746685,582.578125,73.9921875 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+llama-2-70b-chat,10.0,2.6760833263397217,165.55,25.2 +llama-2-70b-chat,11.0,3.1485369634628295,298.56666666666666,45.766666666666666 +llama-2-70b-chat,12.0,4.026921252409617,294.06,42.54 +llama-2-70b-chat,13.0,4.110724348770945,428.7375,65.5375 +llama-2-70b-chat,14.0,4.592028452555339,423.8875,60.8125 +llama-2-70b-chat,15.0,2.76978215304288,285.925,44.15 +llama-2-70b-chat,16.0,4.2957686424255375,572.3083333333333,74.625 +llama-2-70b-chat,17.0,2.720098500781589,254.86666666666667,39.28333333333333 +llama-2-70b-chat,18.0,2.9921934604644775,326.375,50.025 +llama-2-70b-chat,19.0,2.7523183100151294,283.95,43.8375 +llama-2-70b-chat,20.0,3.1451149598146095,345.975,49.65 +llama-2-70b-chat,21.0,4.558388976727501,556.1583333333333,71.875 +llama-2-70b-chat,22.0,3.0530899854806752,348.0,53.65 +llama-2-70b-chat,23.0,2.941225928068161,355.5,54.75 +zephyr-7b-beta,0.0,,, +zephyr-7b-beta,1.0,1.9264068841934203,29.75,3.3 +zephyr-7b-beta,2.0,,, +zephyr-7b-beta,3.0,,, +zephyr-7b-beta,4.0,,, +zephyr-7b-beta,5.0,,, +zephyr-7b-beta,6.0,,, +zephyr-7b-beta,7.0,,, +zephyr-7b-beta,8.0,,, +zephyr-7b-beta,9.0,,, +zephyr-7b-beta,10.0,,, +zephyr-7b-beta,11.0,4.056525647640228,386.3,63.35 +zephyr-7b-beta,12.0,3.3402509868144987,216.9,33.575 +zephyr-7b-beta,13.0,,, +zephyr-7b-beta,14.0,4.056431210041046,399.0,64.9 +zephyr-7b-beta,15.0,4.06974081993103,386.3,63.35 +zephyr-7b-beta,16.0,3.304698485362379,214.1625,32.7875 +zephyr-7b-beta,17.0,,, +zephyr-7b-beta,18.0,4.079625189304352,386.3,63.35 +zephyr-7b-beta,19.0,,, +zephyr-7b-beta,20.0,3.3111458659172057,216.9,33.575 +zephyr-7b-beta,21.0,3.339973047375679,219.1875,33.6875 +zephyr-7b-beta,22.0,,, +zephyr-7b-beta,23.0,,, diff --git a/data/2024-02-03 22:30:15.856748_time_of_day_comparison.csv b/data/2024-02-03 22:30:15.856748_time_of_day_comparison.csv new file mode 100644 index 0000000000000000000000000000000000000000..b9d516ad920187ccea4da16935ba9394656344c2 --- /dev/null +++ b/data/2024-02-03 22:30:15.856748_time_of_day_comparison.csv @@ -0,0 +1,91 @@ +model,time,execution_time,characters_count,words_count +Mistral-7B-Instruct-v0.2,afternoon 12-14,3.228973722457886,222.0625,32.25 +Mistral-7B-Instruct-v0.2,early morning 6-8,,, +Mistral-7B-Instruct-v0.2,evening 18-20,3.397640073299408,261.18333333333334,40.1 +Mistral-7B-Instruct-v0.2,late afternoon 15-17,3.2048643112182615,219.8625,31.8 +Mistral-7B-Instruct-v0.2,morning 9-11,3.734026002883911,362.9,58.35 +Mistral-7B-Instruct-v0.2,night 0-2,1.9149879813194275,37.8,2.95 +Mistral-7B-Instruct-v0.2,night 21-23,3.389284573495388,175.79375,25.68125 +Mistral-7B-Instruct-v0.2,night 3-5,,, +Mixtral-8x7B-Instruct-v0.1,afternoon 12-14,5.362903979589355,369.3192307692308,54.353846153846156 +Mixtral-8x7B-Instruct-v0.1,early morning 6-8,3.2748278152374994,243.2642857142857,37.57857142857143 +Mixtral-8x7B-Instruct-v0.1,evening 18-20,3.6435119574237023,326.69,48.545 +Mixtral-8x7B-Instruct-v0.1,late afternoon 15-17,5.80184749175942,347.9681818181818,47.27272727272727 +Mixtral-8x7B-Instruct-v0.1,morning 9-11,3.9661054956285575,304.82,47.28 +Mixtral-8x7B-Instruct-v0.1,night 0-2,3.8265925436529495,362.25625,52.85625 +Mixtral-8x7B-Instruct-v0.1,night 21-23,5.62397656769588,395.15714285714284,49.02857142857143 +Mixtral-8x7B-Instruct-v0.1,night 3-5,3.010503646099206,262.8,40.56 +TinyLlama/TinyLlama-1.1B-Chat-v1.0,afternoon 12-14,1.8381905496120452,308.795,51.08 +TinyLlama/TinyLlama-1.1B-Chat-v1.0,early morning 6-8,2.0273348593711855,372.13,62.53 +TinyLlama/TinyLlama-1.1B-Chat-v1.0,evening 18-20,1.7984187936782836,313.99,51.96 +TinyLlama/TinyLlama-1.1B-Chat-v1.0,late afternoon 15-17,1.7547113946505954,285.17857142857144,46.9 +TinyLlama/TinyLlama-1.1B-Chat-v1.0,morning 9-11,1.9041210174560548,372.05,62.6 +TinyLlama/TinyLlama-1.1B-Chat-v1.0,night 0-2,1.6341248273849487,210.2,34.2 +TinyLlama/TinyLlama-1.1B-Chat-v1.0,night 21-23,1.5875422928068372,192.78333333333333,31.261111111111113 +TinyLlama/TinyLlama-1.1B-Chat-v1.0,night 3-5,2.0128010153770446,372.05,62.6 +chat-bison,night 0-2,3.890243631601334,398.075,49.0 +chat-bison (PaLM 2),afternoon 12-14,2.6460144804074215,376.28076923076924,55.965384615384615 +chat-bison (PaLM 2),early morning 6-8,2.4665334616388592,381.9214285714286,60.892857142857146 +chat-bison (PaLM 2),evening 18-20,2.688272579908371,367.07,55.89 +chat-bison (PaLM 2),late afternoon 15-17,3.0387172081253744,381.1363636363636,53.35454545454545 +chat-bison (PaLM 2),morning 9-11,2.488477897644043,381.73,60.88 +chat-bison (PaLM 2),night 0-2,2.468383938074112,381.95,60.9 +chat-bison (PaLM 2),night 21-23,2.7250528037548065,382.725,52.95 +chat-bison (PaLM 2),night 3-5,2.460119960308075,381.92,60.94 +chat-bison-32k,night 0-2,4.128177767992019,389.925,48.025 +chat-bison-32k (PaLM 2 32K),afternoon 12-14,5.014458654477046,339.3692307692308,49.323076923076925 +chat-bison-32k (PaLM 2 32K),early morning 6-8,9.141417106560299,335.75,53.85 +chat-bison-32k (PaLM 2 32K),evening 18-20,7.7332194912433625,329.46,49.5 +chat-bison-32k (PaLM 2 32K),late afternoon 15-17,4.5047362284226855,348.65909090909093,48.35454545454545 +chat-bison-32k (PaLM 2 32K),morning 9-11,7.7035503840446475,335.75,53.85 +chat-bison-32k (PaLM 2 32K),night 0-2,7.7498266498247785,335.75,53.85 +chat-bison-32k (PaLM 2 32K),night 21-23,7.796841062307358,349.95,47.805 +chat-bison-32k (PaLM 2 32K),night 3-5,6.491292915344238,335.75,53.85 +gemini-pro,afternoon 12-14,2.816922114008949,360.62307692307695,53.25769230769231 +gemini-pro,early morning 6-8,2.7453590130460435,381.2214285714286,60.964285714285715 +gemini-pro,evening 18-20,2.86901999375759,366.4,55.045 +gemini-pro,late afternoon 15-17,2.9268629640903114,364.57272727272726,50.1 +gemini-pro,morning 9-11,2.497767536007628,371.93,59.39 +gemini-pro,night 0-2,3.338477972348531,369.825,55.9125 +gemini-pro,night 21-23,3.7189874940246117,390.9142857142857,51.35 +gemini-pro,night 3-5,2.8375814715210272,374.8,60.04 +gpt-3.5-turbo,afternoon 12-14,3.9458200880459375,381.4428571428571,43.76190476190476 +gpt-3.5-turbo,early morning 6-8,3.787998208734724,403.74444444444447,47.34444444444444 +gpt-3.5-turbo,evening 18-20,3.5153889304115657,385.18095238095236,46.01428571428571 +gpt-3.5-turbo,late afternoon 15-17,4.384064777692159,396.4357142857143,43.28333333333333 +gpt-3.5-turbo,morning 9-11,3.126271222697364,389.9888888888889,50.93888888888889 +gpt-3.5-turbo,night 0-2,3.822115447632102,426.71923076923076,49.05 +gpt-3.5-turbo,night 21-23,5.110168156187617,422.73510971786834,45.358934169278996 +gpt-3.5-turbo,night 3-5,6.062970260473398,418.6192307692308,44.926923076923075 +gpt-4,afternoon 12-14,16.002364798386893,318.3095238095238,38.77142857142857 +gpt-4,early morning 6-8,14.348626694414351,323.5388888888889,40.544444444444444 +gpt-4,evening 18-20,13.841120740345547,318.0809523809524,40.19285714285714 +gpt-4,late afternoon 15-17,16.80607506932254,313.3595238095238,37.49285714285714 +gpt-4,morning 9-11,12.759107512468733,338.18333333333334,46.85 +gpt-4,night 0-2,12.3578163115329,334.075,41.35 +gpt-4,night 21-23,14.298642643005493,314.336,37.012 +gpt-4,night 3-5,12.813134506115546,316.93461538461537,37.93076923076923 +gpt-4-turbo,afternoon 12-14,13.997754749229976,351.01190476190476,46.03333333333333 +gpt-4-turbo,early morning 6-8,11.555620827939775,357.65555555555557,47.21666666666667 +gpt-4-turbo,evening 18-20,16.550320884159632,382.31666666666666,48.45 +gpt-4-turbo,late afternoon 15-17,22.320911452883767,381.65714285714284,47.35476190476191 +gpt-4-turbo,morning 9-11,13.686854598257277,381.8888888888889,55.02777777777778 +gpt-4-turbo,night 0-2,13.770663784850727,382.7613636363636,47.61818181818182 +gpt-4-turbo,night 21-23,14.592236209392548,413.61,44.8 +gpt-4-turbo,night 3-5,14.254795966698573,352.54615384615386,46.37692307692308 +llama-2-70b-chat,afternoon 12-14,4.234376892130426,375.44615384615383,55.238461538461536 +llama-2-70b-chat,early morning 6-8,2.8660141522424265,289.6642857142857,44.614285714285714 +llama-2-70b-chat,evening 18-20,2.9706250462084185,317.245,47.4 +llama-2-70b-chat,late afternoon 15-17,3.6833307104881365,433.6636363636364,59.445454545454545 +llama-2-70b-chat,morning 9-11,2.872361832027194,283.35,43.45 +llama-2-70b-chat,night 0-2,3.249819871626402,346.8875,52.06875 +llama-2-70b-chat,night 21-23,4.719581684340602,572.1689655172414,79.83103448275862 +llama-2-70b-chat,night 3-5,2.8264514451677147,313.71,48.42 +zephyr-7b-beta,afternoon 12-14,3.5789777278900146,277.6,44.016666666666666 +zephyr-7b-beta,early morning 6-8,,, +zephyr-7b-beta,evening 18-20,3.5673056403795878,273.3666666666667,43.5 +zephyr-7b-beta,late afternoon 15-17,3.4592524923459447,248.59,38.9 +zephyr-7b-beta,morning 9-11,4.056525647640228,386.3,63.35 +zephyr-7b-beta,night 0-2,1.9264068841934203,29.75,3.3 +zephyr-7b-beta,night 21-23,3.45343524068594,176.23125,27.21875 +zephyr-7b-beta,night 3-5,,, diff --git a/data/2024-02-03 22:31:14.132394_time_of_day_comparison.csv b/data/2024-02-03 22:31:14.132394_time_of_day_comparison.csv new file mode 100644 index 0000000000000000000000000000000000000000..28a8d10a8415887d55cc67369a3d161d2b470dc2 --- /dev/null +++ b/data/2024-02-03 22:31:14.132394_time_of_day_comparison.csv @@ -0,0 +1,91 @@ +model,time_of_day,execution_time,characters_count,words_count +Mistral-7B-Instruct-v0.2,afternoon 12-14,3.228973722457886,222.0625,32.25 +Mistral-7B-Instruct-v0.2,early morning 6-8,,, +Mistral-7B-Instruct-v0.2,evening 18-20,3.397640073299408,261.18333333333334,40.1 +Mistral-7B-Instruct-v0.2,late afternoon 15-17,3.2048643112182615,219.8625,31.8 +Mistral-7B-Instruct-v0.2,morning 9-11,3.734026002883911,362.9,58.35 +Mistral-7B-Instruct-v0.2,night 0-2,1.9149879813194275,37.8,2.95 +Mistral-7B-Instruct-v0.2,night 21-23,3.389284573495388,175.79375,25.68125 +Mistral-7B-Instruct-v0.2,night 3-5,,, +Mixtral-8x7B-Instruct-v0.1,afternoon 12-14,5.362903979589355,369.3192307692308,54.353846153846156 +Mixtral-8x7B-Instruct-v0.1,early morning 6-8,3.2748278152374994,243.2642857142857,37.57857142857143 +Mixtral-8x7B-Instruct-v0.1,evening 18-20,3.6435119574237023,326.69,48.545 +Mixtral-8x7B-Instruct-v0.1,late afternoon 15-17,5.80184749175942,347.9681818181818,47.27272727272727 +Mixtral-8x7B-Instruct-v0.1,morning 9-11,3.9661054956285575,304.82,47.28 +Mixtral-8x7B-Instruct-v0.1,night 0-2,3.8265925436529495,362.25625,52.85625 +Mixtral-8x7B-Instruct-v0.1,night 21-23,5.62397656769588,395.15714285714284,49.02857142857143 +Mixtral-8x7B-Instruct-v0.1,night 3-5,3.010503646099206,262.8,40.56 +TinyLlama/TinyLlama-1.1B-Chat-v1.0,afternoon 12-14,1.8381905496120452,308.795,51.08 +TinyLlama/TinyLlama-1.1B-Chat-v1.0,early morning 6-8,2.0273348593711855,372.13,62.53 +TinyLlama/TinyLlama-1.1B-Chat-v1.0,evening 18-20,1.7984187936782836,313.99,51.96 +TinyLlama/TinyLlama-1.1B-Chat-v1.0,late afternoon 15-17,1.7547113946505954,285.17857142857144,46.9 +TinyLlama/TinyLlama-1.1B-Chat-v1.0,morning 9-11,1.9041210174560548,372.05,62.6 +TinyLlama/TinyLlama-1.1B-Chat-v1.0,night 0-2,1.6341248273849487,210.2,34.2 +TinyLlama/TinyLlama-1.1B-Chat-v1.0,night 21-23,1.5875422928068372,192.78333333333333,31.261111111111113 +TinyLlama/TinyLlama-1.1B-Chat-v1.0,night 3-5,2.0128010153770446,372.05,62.6 +chat-bison,night 0-2,3.890243631601334,398.075,49.0 +chat-bison (PaLM 2),afternoon 12-14,2.6460144804074215,376.28076923076924,55.965384615384615 +chat-bison (PaLM 2),early morning 6-8,2.4665334616388592,381.9214285714286,60.892857142857146 +chat-bison (PaLM 2),evening 18-20,2.688272579908371,367.07,55.89 +chat-bison (PaLM 2),late afternoon 15-17,3.0387172081253744,381.1363636363636,53.35454545454545 +chat-bison (PaLM 2),morning 9-11,2.488477897644043,381.73,60.88 +chat-bison (PaLM 2),night 0-2,2.468383938074112,381.95,60.9 +chat-bison (PaLM 2),night 21-23,2.7250528037548065,382.725,52.95 +chat-bison (PaLM 2),night 3-5,2.460119960308075,381.92,60.94 +chat-bison-32k,night 0-2,4.128177767992019,389.925,48.025 +chat-bison-32k (PaLM 2 32K),afternoon 12-14,5.014458654477046,339.3692307692308,49.323076923076925 +chat-bison-32k (PaLM 2 32K),early morning 6-8,9.141417106560299,335.75,53.85 +chat-bison-32k (PaLM 2 32K),evening 18-20,7.7332194912433625,329.46,49.5 +chat-bison-32k (PaLM 2 32K),late afternoon 15-17,4.5047362284226855,348.65909090909093,48.35454545454545 +chat-bison-32k (PaLM 2 32K),morning 9-11,7.7035503840446475,335.75,53.85 +chat-bison-32k (PaLM 2 32K),night 0-2,7.7498266498247785,335.75,53.85 +chat-bison-32k (PaLM 2 32K),night 21-23,7.796841062307358,349.95,47.805 +chat-bison-32k (PaLM 2 32K),night 3-5,6.491292915344238,335.75,53.85 +gemini-pro,afternoon 12-14,2.816922114008949,360.62307692307695,53.25769230769231 +gemini-pro,early morning 6-8,2.7453590130460435,381.2214285714286,60.964285714285715 +gemini-pro,evening 18-20,2.86901999375759,366.4,55.045 +gemini-pro,late afternoon 15-17,2.9268629640903114,364.57272727272726,50.1 +gemini-pro,morning 9-11,2.497767536007628,371.93,59.39 +gemini-pro,night 0-2,3.338477972348531,369.825,55.9125 +gemini-pro,night 21-23,3.7189874940246117,390.9142857142857,51.35 +gemini-pro,night 3-5,2.8375814715210272,374.8,60.04 +gpt-3.5-turbo,afternoon 12-14,3.9458200880459375,381.4428571428571,43.76190476190476 +gpt-3.5-turbo,early morning 6-8,3.787998208734724,403.74444444444447,47.34444444444444 +gpt-3.5-turbo,evening 18-20,3.5153889304115657,385.18095238095236,46.01428571428571 +gpt-3.5-turbo,late afternoon 15-17,4.384064777692159,396.4357142857143,43.28333333333333 +gpt-3.5-turbo,morning 9-11,3.126271222697364,389.9888888888889,50.93888888888889 +gpt-3.5-turbo,night 0-2,3.822115447632102,426.71923076923076,49.05 +gpt-3.5-turbo,night 21-23,5.110168156187617,422.73510971786834,45.358934169278996 +gpt-3.5-turbo,night 3-5,6.062970260473398,418.6192307692308,44.926923076923075 +gpt-4,afternoon 12-14,16.002364798386893,318.3095238095238,38.77142857142857 +gpt-4,early morning 6-8,14.348626694414351,323.5388888888889,40.544444444444444 +gpt-4,evening 18-20,13.841120740345547,318.0809523809524,40.19285714285714 +gpt-4,late afternoon 15-17,16.80607506932254,313.3595238095238,37.49285714285714 +gpt-4,morning 9-11,12.759107512468733,338.18333333333334,46.85 +gpt-4,night 0-2,12.3578163115329,334.075,41.35 +gpt-4,night 21-23,14.298642643005493,314.336,37.012 +gpt-4,night 3-5,12.813134506115546,316.93461538461537,37.93076923076923 +gpt-4-turbo,afternoon 12-14,13.997754749229976,351.01190476190476,46.03333333333333 +gpt-4-turbo,early morning 6-8,11.555620827939775,357.65555555555557,47.21666666666667 +gpt-4-turbo,evening 18-20,16.550320884159632,382.31666666666666,48.45 +gpt-4-turbo,late afternoon 15-17,22.320911452883767,381.65714285714284,47.35476190476191 +gpt-4-turbo,morning 9-11,13.686854598257277,381.8888888888889,55.02777777777778 +gpt-4-turbo,night 0-2,13.770663784850727,382.7613636363636,47.61818181818182 +gpt-4-turbo,night 21-23,14.592236209392548,413.61,44.8 +gpt-4-turbo,night 3-5,14.254795966698573,352.54615384615386,46.37692307692308 +llama-2-70b-chat,afternoon 12-14,4.234376892130426,375.44615384615383,55.238461538461536 +llama-2-70b-chat,early morning 6-8,2.8660141522424265,289.6642857142857,44.614285714285714 +llama-2-70b-chat,evening 18-20,2.9706250462084185,317.245,47.4 +llama-2-70b-chat,late afternoon 15-17,3.6833307104881365,433.6636363636364,59.445454545454545 +llama-2-70b-chat,morning 9-11,2.872361832027194,283.35,43.45 +llama-2-70b-chat,night 0-2,3.249819871626402,346.8875,52.06875 +llama-2-70b-chat,night 21-23,4.719581684340602,572.1689655172414,79.83103448275862 +llama-2-70b-chat,night 3-5,2.8264514451677147,313.71,48.42 +zephyr-7b-beta,afternoon 12-14,3.5789777278900146,277.6,44.016666666666666 +zephyr-7b-beta,early morning 6-8,,, +zephyr-7b-beta,evening 18-20,3.5673056403795878,273.3666666666667,43.5 +zephyr-7b-beta,late afternoon 15-17,3.4592524923459447,248.59,38.9 +zephyr-7b-beta,morning 9-11,4.056525647640228,386.3,63.35 +zephyr-7b-beta,night 0-2,1.9264068841934203,29.75,3.3 +zephyr-7b-beta,night 21-23,3.45343524068594,176.23125,27.21875 +zephyr-7b-beta,night 3-5,,, diff --git a/data/2024-02-03 22:33:36.957992_time_of_day_comparison.csv b/data/2024-02-03 22:33:36.957992_time_of_day_comparison.csv new file mode 100644 index 0000000000000000000000000000000000000000..1bfa7b9d1951e642677bd03c6715a816c6b4e199 --- /dev/null +++ b/data/2024-02-03 22:33:36.957992_time_of_day_comparison.csv @@ -0,0 +1,91 @@ +model,time_of_day,execution_time,characters_count,words_count +Mistral-7B-Instruct-v0.2,0-2 midnight,1.9149879813194275,37.8,2.95 +Mistral-7B-Instruct-v0.2,12-14 afternoon,3.228973722457886,222.0625,32.25 +Mistral-7B-Instruct-v0.2,15-17 late afternoon,3.2048643112182615,219.8625,31.8 +Mistral-7B-Instruct-v0.2,18-20 evening,3.397640073299408,261.18333333333334,40.1 +Mistral-7B-Instruct-v0.2,21-23 late evening,3.389284573495388,175.79375,25.68125 +Mistral-7B-Instruct-v0.2,3-5 night,,, +Mistral-7B-Instruct-v0.2,6-8 early morning,,, +Mistral-7B-Instruct-v0.2,9-11 morning,3.734026002883911,362.9,58.35 +Mixtral-8x7B-Instruct-v0.1,0-2 midnight,3.8265925436529495,362.25625,52.85625 +Mixtral-8x7B-Instruct-v0.1,12-14 afternoon,5.362903979589355,369.3192307692308,54.353846153846156 +Mixtral-8x7B-Instruct-v0.1,15-17 late afternoon,5.80184749175942,347.9681818181818,47.27272727272727 +Mixtral-8x7B-Instruct-v0.1,18-20 evening,3.6435119574237023,326.69,48.545 +Mixtral-8x7B-Instruct-v0.1,21-23 late evening,5.62397656769588,395.15714285714284,49.02857142857143 +Mixtral-8x7B-Instruct-v0.1,3-5 night,3.010503646099206,262.8,40.56 +Mixtral-8x7B-Instruct-v0.1,6-8 early morning,3.2748278152374994,243.2642857142857,37.57857142857143 +Mixtral-8x7B-Instruct-v0.1,9-11 morning,3.9661054956285575,304.82,47.28 +TinyLlama/TinyLlama-1.1B-Chat-v1.0,0-2 midnight,1.6341248273849487,210.2,34.2 +TinyLlama/TinyLlama-1.1B-Chat-v1.0,12-14 afternoon,1.8381905496120452,308.795,51.08 +TinyLlama/TinyLlama-1.1B-Chat-v1.0,15-17 late afternoon,1.7547113946505954,285.17857142857144,46.9 +TinyLlama/TinyLlama-1.1B-Chat-v1.0,18-20 evening,1.7984187936782836,313.99,51.96 +TinyLlama/TinyLlama-1.1B-Chat-v1.0,21-23 late evening,1.5875422928068372,192.78333333333333,31.261111111111113 +TinyLlama/TinyLlama-1.1B-Chat-v1.0,3-5 night,2.0128010153770446,372.05,62.6 +TinyLlama/TinyLlama-1.1B-Chat-v1.0,6-8 early morning,2.0273348593711855,372.13,62.53 +TinyLlama/TinyLlama-1.1B-Chat-v1.0,9-11 morning,1.9041210174560548,372.05,62.6 +chat-bison,0-2 midnight,3.890243631601334,398.075,49.0 +chat-bison (PaLM 2),0-2 midnight,2.468383938074112,381.95,60.9 +chat-bison (PaLM 2),12-14 afternoon,2.6460144804074215,376.28076923076924,55.965384615384615 +chat-bison (PaLM 2),15-17 late afternoon,3.0387172081253744,381.1363636363636,53.35454545454545 +chat-bison (PaLM 2),18-20 evening,2.688272579908371,367.07,55.89 +chat-bison (PaLM 2),21-23 late evening,2.7250528037548065,382.725,52.95 +chat-bison (PaLM 2),3-5 night,2.460119960308075,381.92,60.94 +chat-bison (PaLM 2),6-8 early morning,2.4665334616388592,381.9214285714286,60.892857142857146 +chat-bison (PaLM 2),9-11 morning,2.488477897644043,381.73,60.88 +chat-bison-32k,0-2 midnight,4.128177767992019,389.925,48.025 +chat-bison-32k (PaLM 2 32K),0-2 midnight,7.7498266498247785,335.75,53.85 +chat-bison-32k (PaLM 2 32K),12-14 afternoon,5.014458654477046,339.3692307692308,49.323076923076925 +chat-bison-32k (PaLM 2 32K),15-17 late afternoon,4.5047362284226855,348.65909090909093,48.35454545454545 +chat-bison-32k (PaLM 2 32K),18-20 evening,7.7332194912433625,329.46,49.5 +chat-bison-32k (PaLM 2 32K),21-23 late evening,7.796841062307358,349.95,47.805 +chat-bison-32k (PaLM 2 32K),3-5 night,6.491292915344238,335.75,53.85 +chat-bison-32k (PaLM 2 32K),6-8 early morning,9.141417106560299,335.75,53.85 +chat-bison-32k (PaLM 2 32K),9-11 morning,7.7035503840446475,335.75,53.85 +gemini-pro,0-2 midnight,3.338477972348531,369.825,55.9125 +gemini-pro,12-14 afternoon,2.816922114008949,360.62307692307695,53.25769230769231 +gemini-pro,15-17 late afternoon,2.9268629640903114,364.57272727272726,50.1 +gemini-pro,18-20 evening,2.86901999375759,366.4,55.045 +gemini-pro,21-23 late evening,3.7189874940246117,390.9142857142857,51.35 +gemini-pro,3-5 night,2.8375814715210272,374.8,60.04 +gemini-pro,6-8 early morning,2.7453590130460435,381.2214285714286,60.964285714285715 +gemini-pro,9-11 morning,2.497767536007628,371.93,59.39 +gpt-3.5-turbo,0-2 midnight,3.822115447632102,426.71923076923076,49.05 +gpt-3.5-turbo,12-14 afternoon,3.9458200880459375,381.4428571428571,43.76190476190476 +gpt-3.5-turbo,15-17 late afternoon,4.384064777692159,396.4357142857143,43.28333333333333 +gpt-3.5-turbo,18-20 evening,3.5153889304115657,385.18095238095236,46.01428571428571 +gpt-3.5-turbo,21-23 late evening,5.110168156187617,422.73510971786834,45.358934169278996 +gpt-3.5-turbo,3-5 night,6.062970260473398,418.6192307692308,44.926923076923075 +gpt-3.5-turbo,6-8 early morning,3.787998208734724,403.74444444444447,47.34444444444444 +gpt-3.5-turbo,9-11 morning,3.126271222697364,389.9888888888889,50.93888888888889 +gpt-4,0-2 midnight,12.3578163115329,334.075,41.35 +gpt-4,12-14 afternoon,16.002364798386893,318.3095238095238,38.77142857142857 +gpt-4,15-17 late afternoon,16.80607506932254,313.3595238095238,37.49285714285714 +gpt-4,18-20 evening,13.841120740345547,318.0809523809524,40.19285714285714 +gpt-4,21-23 late evening,14.298642643005493,314.336,37.012 +gpt-4,3-5 night,12.813134506115546,316.93461538461537,37.93076923076923 +gpt-4,6-8 early morning,14.348626694414351,323.5388888888889,40.544444444444444 +gpt-4,9-11 morning,12.759107512468733,338.18333333333334,46.85 +gpt-4-turbo,0-2 midnight,13.770663784850727,382.7613636363636,47.61818181818182 +gpt-4-turbo,12-14 afternoon,13.997754749229976,351.01190476190476,46.03333333333333 +gpt-4-turbo,15-17 late afternoon,22.320911452883767,381.65714285714284,47.35476190476191 +gpt-4-turbo,18-20 evening,16.550320884159632,382.31666666666666,48.45 +gpt-4-turbo,21-23 late evening,14.592236209392548,413.61,44.8 +gpt-4-turbo,3-5 night,14.254795966698573,352.54615384615386,46.37692307692308 +gpt-4-turbo,6-8 early morning,11.555620827939775,357.65555555555557,47.21666666666667 +gpt-4-turbo,9-11 morning,13.686854598257277,381.8888888888889,55.02777777777778 +llama-2-70b-chat,0-2 midnight,3.249819871626402,346.8875,52.06875 +llama-2-70b-chat,12-14 afternoon,4.234376892130426,375.44615384615383,55.238461538461536 +llama-2-70b-chat,15-17 late afternoon,3.6833307104881365,433.6636363636364,59.445454545454545 +llama-2-70b-chat,18-20 evening,2.9706250462084185,317.245,47.4 +llama-2-70b-chat,21-23 late evening,4.719581684340602,572.1689655172414,79.83103448275862 +llama-2-70b-chat,3-5 night,2.8264514451677147,313.71,48.42 +llama-2-70b-chat,6-8 early morning,2.8660141522424265,289.6642857142857,44.614285714285714 +llama-2-70b-chat,9-11 morning,2.872361832027194,283.35,43.45 +zephyr-7b-beta,0-2 midnight,1.9264068841934203,29.75,3.3 +zephyr-7b-beta,12-14 afternoon,3.5789777278900146,277.6,44.016666666666666 +zephyr-7b-beta,15-17 late afternoon,3.4592524923459447,248.59,38.9 +zephyr-7b-beta,18-20 evening,3.5673056403795878,273.3666666666667,43.5 +zephyr-7b-beta,21-23 late evening,3.45343524068594,176.23125,27.21875 +zephyr-7b-beta,3-5 night,,, +zephyr-7b-beta,6-8 early morning,,, +zephyr-7b-beta,9-11 morning,4.056525647640228,386.3,63.35 diff --git a/data/2024-02-03 22:42:23.322179_summary.csv b/data/2024-02-03 22:42:23.322179_summary.csv new file mode 100644 index 0000000000000000000000000000000000000000..761e8fd47df67b529ed8b02afdf6fa129fe7fb7a --- /dev/null +++ b/data/2024-02-03 22:42:23.322179_summary.csv @@ -0,0 +1,75 @@ +model,language,template_name,execution_time,characters_count,words_count,chunk_sizes_mean,chunk_sizes_min,chunk_sizes_max,chunk_generation_times_mean,chunk_generation_times_min,chunk_generation_times_max +Mistral-7B-Instruct-v0.2,english,call,,,,,,,,, +Mistral-7B-Instruct-v0.2,english,json,4.278648148264204,342.8,55.15,4.1311870534561415,1.0,15.0,0.040544769239987996,0.00024437904357910156,60.7178213596344 +Mistral-7B-Instruct-v0.2,english,markdown,3.7188014924526214,366.85,57.1375,4.239202657807309,1.0,16.0,0.03371991898375372,0.020945072174072266,0.25538039207458496 +Mistral-7B-Instruct-v0.2,japanese,call,,,,,,,,, +Mistral-7B-Instruct-v0.2,japanese,json,2.413569121701377,52.07857142857143,3.414285714285714,1.2991803278688525,1.0,11.0,0.039267738759305254,0.00047779083251953125,3.370748996734619 +Mistral-7B-Instruct-v0.2,japanese,markdown,2.323612022399902,42.25,1.5833333333333333,1.1069868995633187,1.0,6.0,0.03958142719935121,0.0004932880401611328,0.2205650806427002 +Mixtral-8x7B-Instruct-v0.1,english,call,,,,,,,,, +Mixtral-8x7B-Instruct-v0.1,english,json,3.643989532061343,295.4172413793103,45.744827586206895,4.137546333747872,1.0,15.0,0.014243678199270911,0.00020456314086914062,3.4127349853515625 +Mixtral-8x7B-Instruct-v0.1,english,markdown,5.995457515120506,512.57,81.75,4.360071452875127,1.0,15.0,0.016480832612607788,0.00021076202392578125,1.7103569507598877 +Mixtral-8x7B-Instruct-v0.1,japanese,call,,,,,,,,, +Mixtral-8x7B-Instruct-v0.1,japanese,json,7.938035423738243,553.5285714285715,63.378571428571426,2.248940739450926,1.0,109.0,0.023964353726961752,0.00020885467529296875,76.45081758499146 +Mixtral-8x7B-Instruct-v0.1,japanese,markdown,9.979603266716003,431.71666666666664,5.983333333333333,1.0810483702683527,1.0,12.0,0.017558807731893653,0.0002148151397705078,2.994176149368286 +TinyLlama/TinyLlama-1.1B-Chat-v1.0,english,call,,,,,,,,, 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23:33:22.947120_summary.csv @@ -0,0 +1,55 @@ +model,language,template_name,execution_time,characters_count,words_count,chunk_sizes_mean,chunk_sizes_min,chunk_sizes_max,chunk_generation_times_mean,chunk_generation_times_min,chunk_generation_times_max +Mistral-7B-Instruct-v0.2,english,json,4.278648148264204,342.8,55.15,4.1311870534561415,1.0,15.0,0.040544769239987996,0.00024437904357910156,60.7178213596344 +Mistral-7B-Instruct-v0.2,english,markdown,3.7188014924526214,366.85,57.1375,4.239202657807309,1.0,16.0,0.03371991898375372,0.020945072174072266,0.25538039207458496 +Mistral-7B-Instruct-v0.2,japanese,json,2.413569121701377,52.07857142857143,3.414285714285714,1.2991803278688525,1.0,11.0,0.039267738759305254,0.00047779083251953125,3.370748996734619 +Mistral-7B-Instruct-v0.2,japanese,markdown,2.323612022399902,42.25,1.5833333333333333,1.1069868995633187,1.0,6.0,0.03958142719935121,0.0004932880401611328,0.2205650806427002 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+gemini-pro,japanese,json,4.5300196591070145,276.6694915254237,6.983050847457627,91.1927374301676,4.0,333.0,1.4752027082709627,0.0006062984466552734,8.291066646575928 +gemini-pro,japanese,markdown,6.166934008781727,422.7307692307692,9.096153846153847,90.83471074380165,9.0,266.0,1.3123543331445742,0.0006639957427978516,13.754565954208374 +gpt-3.5-turbo,english,call,2.908525016600803,456.85911016949154,72.26059322033899,,,,,, +gpt-3.5-turbo,english,json,2.566863525494622,398.56960556844547,65.32366589327147,4.806746320443226,1.0,16.0,0.015585779219764062,0.0005395412445068359,1.4500916004180908 +gpt-3.5-turbo,english,markdown,2.3388922008184285,506.90384615384613,81.99038461538461,5.050584403142365,1.0,16.0,0.01715806382989308,0.0005617141723632812,1.127073049545288 +gpt-3.5-turbo,japanese,call,7.255881716940138,382.95,6.351111111111111,,,,,, +gpt-3.5-turbo,japanese,json,5.226112197780009,237.1069182389937,3.559748427672956,1.1291481969569905,1.0,7.0,0.02129129201220198,0.0005452632904052734,13.75982117652893 +gpt-3.5-turbo,japanese,markdown,7.29901300883684,358.72131147540983,6.065573770491803,1.1894977168949772,1.0,15.0,0.021750167313542772,0.0005612373352050781,13.71114993095398 +gpt-4,english,call,9.15708539162022,374.16815144766144,59.661469933184854,,,,,, +gpt-4,english,json,7.963626848197565,383.3707317073171,61.69512195121951,4.7834568389659005,1.0,16.0,0.08687007305138472,0.000537872314453125,3.531284809112549 +gpt-4,english,markdown,10.02310108244419,428.35,67.825,4.990243192078054,1.0,16.0,0.10377185442257747,0.0005447864532470703,2.087376117706299 +gpt-4,japanese,call,24.259297592319243,214.9076023391813,1.1695906432748537,,,,,, +gpt-4,japanese,json,22.703774025460252,211.63025210084032,4.168067226890757,1.1685226429101707,1.0,7.0,0.11835955503744466,0.0005507469177246094,3.5608017444610596 +gpt-4,japanese,markdown,31.99519391655922,275.1,2.925,1.1327980234712787,1.0,9.0,0.12606545905407157,0.0005619525909423828,2.9794347286224365 +gpt-4-turbo,english,call,7.319288367695279,372.86,58.532222222222224,,,,,, +gpt-4-turbo,english,json,6.457074524425879,407.0243902439024,64.18414634146342,4.735998183701559,1.0,17.0,0.06474667943090798,0.0006806850433349609,5.431884765625 +gpt-4-turbo,english,markdown,8.325546002388,462.1125,71.925,4.984360253471754,1.0,16.0,0.07950969425127868,0.0006999969482421875,2.0926766395568848 +gpt-4-turbo,japanese,call,32.67405146055443,372.7860465116279,24.886046511627907,,,,,, +gpt-4-turbo,japanese,json,19.359180968999862,250.44166666666666,6.183333333333334,1.184261339007763,1.0,8.0,0.08582140138847597,0.0006830692291259766,13.252992153167725 +gpt-4-turbo,japanese,markdown,20.977174520492554,283.55,4.45,1.1460038395473375,1.0,10.0,0.07991695286011809,0.0007085800170898438,2.3845231533050537 +llama-2-70b-chat,english,json,2.917410132025375,355.7463556851312,54.861030126336246,4.02267032967033,1.0,15.0,0.019103390617685005,0.0001990795135498047,3.8762006759643555 +llama-2-70b-chat,english,markdown,4.99397261045417,827.5714285714286,125.95918367346938,4.177931176591799,1.0,16.0,0.018161741699259625,0.0002124309539794922,0.7439091205596924 +llama-2-70b-chat,japanese,json,5.265992468681889,369.3768115942029,42.56521739130435,2.3362207250561435,1.0,15.0,0.023359512199899433,0.00020837783813476562,0.9314718246459961 +llama-2-70b-chat,japanese,markdown,11.084085723449444,1379.6896551724137,158.01724137931035,2.2644745033674796,1.0,16.0,0.01566780037868879,0.0002117156982421875,76.44498753547668 +zephyr-7b-beta,english,json,3.94231437737087,367.57232704402514,60.257861635220124,4.262252042007002,1.0,14.0,0.03629181767914927,0.0003070831298828125,0.4896988868713379 +zephyr-7b-beta,english,markdown,4.959704548120499,358.9375,58.3625,4.390672782874618,1.0,15.0,0.05067269182351022,0.00040459632873535156,75.15552616119385 +zephyr-7b-beta,japanese,json,2.339889786640803,41.583333333333336,3.6333333333333333,1.1566991191469633,1.0,7.0,0.042134473762636,0.018090486526489258,0.4599947929382324 +zephyr-7b-beta,japanese,markdown,2.3176693956057233,38.1,2.3833333333333333,1.0343891402714933,1.0,4.0,0.041092377011053165,0.02583909034729004,0.4606599807739258 diff --git a/data/2024-02-06 07:53:19.636658_time_of_day_comparison.csv b/data/2024-02-06 07:53:19.636658_time_of_day_comparison.csv new file mode 100644 index 0000000000000000000000000000000000000000..b28987953bda76f17b8f5e7f697e43a03818f4fa --- /dev/null +++ b/data/2024-02-06 07:53:19.636658_time_of_day_comparison.csv @@ -0,0 +1,91 @@ +model,time_of_day,execution_time,characters_count,words_count +Mistral-7B-Instruct-v0.2,0-2 midnight,1.9149879813194275,37.8,2.95 +Mistral-7B-Instruct-v0.2,12-14 afternoon,3.228973722457886,222.0625,32.25 +Mistral-7B-Instruct-v0.2,15-17 late afternoon,3.2048643112182615,219.8625,31.8 +Mistral-7B-Instruct-v0.2,18-20 evening,3.397640073299408,261.18333333333334,40.1 +Mistral-7B-Instruct-v0.2,21-23 late evening,3.389284573495388,175.79375,25.68125 +Mistral-7B-Instruct-v0.2,3-5 night,,, +Mistral-7B-Instruct-v0.2,6-8 early morning,,, +Mistral-7B-Instruct-v0.2,9-11 morning,3.734026002883911,362.9,58.35 +Mixtral-8x7B-Instruct-v0.1,0-2 midnight,4.639010797279158,323.0394736842105,42.69210526315789 +Mixtral-8x7B-Instruct-v0.1,12-14 afternoon,5.362903979589355,369.3192307692308,54.353846153846156 +Mixtral-8x7B-Instruct-v0.1,15-17 late afternoon,5.80184749175942,347.9681818181818,47.27272727272727 +Mixtral-8x7B-Instruct-v0.1,18-20 evening,3.6435119574237023,326.69,48.545 +Mixtral-8x7B-Instruct-v0.1,21-23 late evening,5.62397656769588,395.15714285714284,49.02857142857143 +Mixtral-8x7B-Instruct-v0.1,3-5 night,4.009439338194697,301.24545454545455,42.21818181818182 +Mixtral-8x7B-Instruct-v0.1,6-8 early morning,4.526968242530536,285.045,41.86 +Mixtral-8x7B-Instruct-v0.1,9-11 morning,3.9661054956285575,304.82,47.28 +TinyLlama/TinyLlama-1.1B-Chat-v1.0,0-2 midnight,1.6341248273849487,210.2,34.2 +TinyLlama/TinyLlama-1.1B-Chat-v1.0,12-14 afternoon,1.8381905496120452,308.795,51.08 +TinyLlama/TinyLlama-1.1B-Chat-v1.0,15-17 late afternoon,1.7547113946505954,285.17857142857144,46.9 +TinyLlama/TinyLlama-1.1B-Chat-v1.0,18-20 evening,1.7984187936782836,313.99,51.96 +TinyLlama/TinyLlama-1.1B-Chat-v1.0,21-23 late evening,1.5875422928068372,192.78333333333333,31.261111111111113 +TinyLlama/TinyLlama-1.1B-Chat-v1.0,3-5 night,2.0128010153770446,372.05,62.6 +TinyLlama/TinyLlama-1.1B-Chat-v1.0,6-8 early morning,2.0273348593711855,372.13,62.53 +TinyLlama/TinyLlama-1.1B-Chat-v1.0,9-11 morning,1.9041210174560548,372.05,62.6 +chat-bison,0-2 midnight,3.890243631601334,398.075,49.0 +chat-bison (PaLM 2),0-2 midnight,2.468383938074112,381.95,60.9 +chat-bison (PaLM 2),12-14 afternoon,2.6460144804074215,376.28076923076924,55.965384615384615 +chat-bison (PaLM 2),15-17 late afternoon,3.0387172081253744,381.1363636363636,53.35454545454545 +chat-bison (PaLM 2),18-20 evening,2.688272579908371,367.07,55.89 +chat-bison (PaLM 2),21-23 late evening,2.7250528037548065,382.725,52.95 +chat-bison (PaLM 2),3-5 night,2.460119960308075,381.92,60.94 +chat-bison (PaLM 2),6-8 early morning,2.4665334616388592,381.9214285714286,60.892857142857146 +chat-bison (PaLM 2),9-11 morning,2.488477897644043,381.73,60.88 +chat-bison-32k,0-2 midnight,4.128177767992019,389.925,48.025 +chat-bison-32k (PaLM 2 32K),0-2 midnight,7.7498266498247785,335.75,53.85 +chat-bison-32k (PaLM 2 32K),12-14 afternoon,5.014458654477046,339.3692307692308,49.323076923076925 +chat-bison-32k (PaLM 2 32K),15-17 late afternoon,4.5047362284226855,348.65909090909093,48.35454545454545 +chat-bison-32k (PaLM 2 32K),18-20 evening,7.7332194912433625,329.46,49.5 +chat-bison-32k (PaLM 2 32K),21-23 late evening,7.796841062307358,349.95,47.805 +chat-bison-32k (PaLM 2 32K),3-5 night,6.491292915344238,335.75,53.85 +chat-bison-32k (PaLM 2 32K),6-8 early morning,9.141417106560299,335.75,53.85 +chat-bison-32k (PaLM 2 32K),9-11 morning,7.7035503840446475,335.75,53.85 +gemini-pro,0-2 midnight,3.338477972348531,369.825,55.9125 +gemini-pro,12-14 afternoon,2.816922114008949,360.62307692307695,53.25769230769231 +gemini-pro,15-17 late afternoon,2.9268629640903114,364.57272727272726,50.1 +gemini-pro,18-20 evening,2.86901999375759,366.4,55.045 +gemini-pro,21-23 late evening,3.7189874940246117,390.9142857142857,51.35 +gemini-pro,3-5 night,2.8375814715210272,374.8,60.04 +gemini-pro,6-8 early morning,2.7453590130460435,381.2214285714286,60.964285714285715 +gemini-pro,9-11 morning,2.497767536007628,371.93,59.39 +gpt-3.5-turbo,0-2 midnight,3.822115447632102,426.71923076923076,49.05 +gpt-3.5-turbo,12-14 afternoon,3.9458200880459375,381.4428571428571,43.76190476190476 +gpt-3.5-turbo,15-17 late afternoon,4.384064777692159,396.4357142857143,43.28333333333333 +gpt-3.5-turbo,18-20 evening,3.5153889304115657,385.18095238095236,46.01428571428571 +gpt-3.5-turbo,21-23 late evening,5.110168156187617,422.73510971786834,45.358934169278996 +gpt-3.5-turbo,3-5 night,6.062970260473398,418.6192307692308,44.926923076923075 +gpt-3.5-turbo,6-8 early morning,3.787998208734724,403.74444444444447,47.34444444444444 +gpt-3.5-turbo,9-11 morning,3.126271222697364,389.9888888888889,50.93888888888889 +gpt-4,0-2 midnight,12.3578163115329,334.075,41.35 +gpt-4,12-14 afternoon,16.002364798386893,318.3095238095238,38.77142857142857 +gpt-4,15-17 late afternoon,16.80607506932254,313.3595238095238,37.49285714285714 +gpt-4,18-20 evening,13.841120740345547,318.0809523809524,40.19285714285714 +gpt-4,21-23 late evening,14.298642643005493,314.336,37.012 +gpt-4,3-5 night,12.813134506115546,316.93461538461537,37.93076923076923 +gpt-4,6-8 early morning,14.348626694414351,323.5388888888889,40.544444444444444 +gpt-4,9-11 morning,12.759107512468733,338.18333333333334,46.85 +gpt-4-turbo,0-2 midnight,13.770663784850727,382.7613636363636,47.61818181818182 +gpt-4-turbo,12-14 afternoon,13.997754749229976,351.01190476190476,46.03333333333333 +gpt-4-turbo,15-17 late afternoon,22.320911452883767,381.65714285714284,47.35476190476191 +gpt-4-turbo,18-20 evening,16.550320884159632,382.31666666666666,48.45 +gpt-4-turbo,21-23 late evening,14.592236209392548,413.61,44.8 +gpt-4-turbo,3-5 night,14.254795966698573,352.54615384615386,46.37692307692308 +gpt-4-turbo,6-8 early morning,11.555620827939775,357.65555555555557,47.21666666666667 +gpt-4-turbo,9-11 morning,13.686854598257277,381.8888888888889,55.02777777777778 +llama-2-70b-chat,0-2 midnight,3.249819871626402,346.8875,52.06875 +llama-2-70b-chat,12-14 afternoon,4.234376892130426,375.44615384615383,55.238461538461536 +llama-2-70b-chat,15-17 late afternoon,3.6833307104881365,433.6636363636364,59.445454545454545 +llama-2-70b-chat,18-20 evening,2.9706250462084185,317.245,47.4 +llama-2-70b-chat,21-23 late evening,4.719581684340602,572.1689655172414,79.83103448275862 +llama-2-70b-chat,3-5 night,2.8264514451677147,313.71,48.42 +llama-2-70b-chat,6-8 early morning,2.8660141522424265,289.6642857142857,44.614285714285714 +llama-2-70b-chat,9-11 morning,2.872361832027194,283.35,43.45 +zephyr-7b-beta,0-2 midnight,3.7253047794103624,217.82083333333333,33.67916666666667 +zephyr-7b-beta,12-14 afternoon,3.5789777278900146,277.6,44.016666666666666 +zephyr-7b-beta,15-17 late afternoon,3.4592524923459447,248.59,38.9 +zephyr-7b-beta,18-20 evening,3.5673056403795878,273.3666666666667,43.5 +zephyr-7b-beta,21-23 late evening,3.45343524068594,176.23125,27.21875 +zephyr-7b-beta,3-5 night,3.6954557319482166,216.55833333333334,33.46666666666667 +zephyr-7b-beta,6-8 early morning,3.937663261095683,273.03333333333336,43.45 +zephyr-7b-beta,9-11 morning,4.056525647640228,386.3,63.35 diff --git a/data/2024-02-06 09:35:10.194145_time_of_day_comparison.csv b/data/2024-02-06 09:35:10.194145_time_of_day_comparison.csv new file mode 100644 index 0000000000000000000000000000000000000000..e838925fb444a77542dd29d60275d67dc191f765 --- /dev/null +++ b/data/2024-02-06 09:35:10.194145_time_of_day_comparison.csv @@ -0,0 +1,89 @@ +model,time_of_day,execution_time,characters_count,words_count +Mistral-7B-Instruct-v0.2,afternoon,3.228973722457886,222.0625,32.25 +Mistral-7B-Instruct-v0.2,evening,3.397640073299408,261.18333333333334,40.1 +Mistral-7B-Instruct-v0.2,late afternoon,3.2048643112182615,219.8625,31.8 +Mistral-7B-Instruct-v0.2,late evening,3.389284573495388,175.79375,25.68125 +Mistral-7B-Instruct-v0.2,midnight,1.9149879813194275,37.8,2.95 +Mistral-7B-Instruct-v0.2,morning,3.734026002883911,362.9,58.35 +Mixtral-8x7B-Instruct-v0.1,afternoon,5.362903979589355,369.3192307692308,54.353846153846156 +Mixtral-8x7B-Instruct-v0.1,early morning,4.526968242530536,285.045,41.86 +Mixtral-8x7B-Instruct-v0.1,evening,3.6435119574237023,326.69,48.545 +Mixtral-8x7B-Instruct-v0.1,late afternoon,5.80184749175942,347.9681818181818,47.27272727272727 +Mixtral-8x7B-Instruct-v0.1,late evening,5.62397656769588,395.15714285714284,49.02857142857143 +Mixtral-8x7B-Instruct-v0.1,midnight,4.639010797279158,323.0394736842105,42.69210526315789 +Mixtral-8x7B-Instruct-v0.1,morning,3.9661054956285575,304.82,47.28 +Mixtral-8x7B-Instruct-v0.1,night,4.009439338194697,301.24545454545455,42.21818181818182 +TinyLlama/TinyLlama-1.1B-Chat-v1.0,afternoon,1.8381905496120452,308.795,51.08 +TinyLlama/TinyLlama-1.1B-Chat-v1.0,early morning,2.0273348593711855,372.13,62.53 +TinyLlama/TinyLlama-1.1B-Chat-v1.0,evening,1.7984187936782836,313.99,51.96 +TinyLlama/TinyLlama-1.1B-Chat-v1.0,late afternoon,1.7547113946505954,285.17857142857144,46.9 +TinyLlama/TinyLlama-1.1B-Chat-v1.0,late evening,1.5875422928068372,192.78333333333333,31.261111111111113 +TinyLlama/TinyLlama-1.1B-Chat-v1.0,midnight,1.6341248273849487,210.2,34.2 +TinyLlama/TinyLlama-1.1B-Chat-v1.0,morning,1.9041210174560548,372.05,62.6 +TinyLlama/TinyLlama-1.1B-Chat-v1.0,night,2.0128010153770446,372.05,62.6 +chat-bison,midnight,3.890243631601334,398.075,49.0 +chat-bison (PaLM 2),afternoon,2.6460144804074215,376.28076923076924,55.965384615384615 +chat-bison (PaLM 2),early morning,2.4665334616388592,381.9214285714286,60.892857142857146 +chat-bison (PaLM 2),evening,2.688272579908371,367.07,55.89 +chat-bison (PaLM 2),late afternoon,3.0387172081253744,381.1363636363636,53.35454545454545 +chat-bison (PaLM 2),late evening,2.7250528037548065,382.725,52.95 +chat-bison (PaLM 2),midnight,2.468383938074112,381.95,60.9 +chat-bison (PaLM 2),morning,2.488477897644043,381.73,60.88 +chat-bison (PaLM 2),night,2.460119960308075,381.92,60.94 +chat-bison-32k,midnight,4.128177767992019,389.925,48.025 +chat-bison-32k (PaLM 2 32K),afternoon,5.014458654477046,339.3692307692308,49.323076923076925 +chat-bison-32k (PaLM 2 32K),early morning,9.141417106560299,335.75,53.85 +chat-bison-32k (PaLM 2 32K),evening,7.7332194912433625,329.46,49.5 +chat-bison-32k (PaLM 2 32K),late afternoon,4.5047362284226855,348.65909090909093,48.35454545454545 +chat-bison-32k (PaLM 2 32K),late evening,7.796841062307358,349.95,47.805 +chat-bison-32k (PaLM 2 32K),midnight,7.7498266498247785,335.75,53.85 +chat-bison-32k (PaLM 2 32K),morning,7.7035503840446475,335.75,53.85 +chat-bison-32k (PaLM 2 32K),night,6.491292915344238,335.75,53.85 +gemini-pro,afternoon,2.816922114008949,360.62307692307695,53.25769230769231 +gemini-pro,early morning,2.7453590130460435,381.2214285714286,60.964285714285715 +gemini-pro,evening,2.86901999375759,366.4,55.045 +gemini-pro,late afternoon,2.9268629640903114,364.57272727272726,50.1 +gemini-pro,late evening,3.7189874940246117,390.9142857142857,51.35 +gemini-pro,midnight,3.338477972348531,369.825,55.9125 +gemini-pro,morning,2.497767536007628,371.93,59.39 +gemini-pro,night,2.8375814715210272,374.8,60.04 +gpt-3.5-turbo,afternoon,3.9458200880459375,381.4428571428571,43.76190476190476 +gpt-3.5-turbo,early morning,3.787998208734724,403.74444444444447,47.34444444444444 +gpt-3.5-turbo,evening,3.5153889304115657,385.18095238095236,46.01428571428571 +gpt-3.5-turbo,late afternoon,4.384064777692159,396.4357142857143,43.28333333333333 +gpt-3.5-turbo,late evening,5.110168156187617,422.73510971786834,45.358934169278996 +gpt-3.5-turbo,midnight,3.822115447632102,426.71923076923076,49.05 +gpt-3.5-turbo,morning,3.126271222697364,389.9888888888889,50.93888888888889 +gpt-3.5-turbo,night,6.062970260473398,418.6192307692308,44.926923076923075 +gpt-4,afternoon,16.002364798386893,318.3095238095238,38.77142857142857 +gpt-4,early morning,14.348626694414351,323.5388888888889,40.544444444444444 +gpt-4,evening,13.841120740345547,318.0809523809524,40.19285714285714 +gpt-4,late afternoon,16.80607506932254,313.3595238095238,37.49285714285714 +gpt-4,late evening,14.298642643005493,314.336,37.012 +gpt-4,midnight,12.3578163115329,334.075,41.35 +gpt-4,morning,12.759107512468733,338.18333333333334,46.85 +gpt-4,night,12.813134506115546,316.93461538461537,37.93076923076923 +gpt-4-turbo,afternoon,13.997754749229976,351.01190476190476,46.03333333333333 +gpt-4-turbo,early morning,11.555620827939775,357.65555555555557,47.21666666666667 +gpt-4-turbo,evening,16.550320884159632,382.31666666666666,48.45 +gpt-4-turbo,late afternoon,22.320911452883767,381.65714285714284,47.35476190476191 +gpt-4-turbo,late evening,14.592236209392548,413.61,44.8 +gpt-4-turbo,midnight,13.770663784850727,382.7613636363636,47.61818181818182 +gpt-4-turbo,morning,13.686854598257277,381.8888888888889,55.02777777777778 +gpt-4-turbo,night,14.254795966698573,352.54615384615386,46.37692307692308 +llama-2-70b-chat,afternoon,4.234376892130426,375.44615384615383,55.238461538461536 +llama-2-70b-chat,early morning,2.8660141522424265,289.6642857142857,44.614285714285714 +llama-2-70b-chat,evening,2.9706250462084185,317.245,47.4 +llama-2-70b-chat,late afternoon,3.6833307104881365,433.6636363636364,59.445454545454545 +llama-2-70b-chat,late evening,4.719581684340602,572.1689655172414,79.83103448275862 +llama-2-70b-chat,midnight,3.249819871626402,346.8875,52.06875 +llama-2-70b-chat,morning,2.872361832027194,283.35,43.45 +llama-2-70b-chat,night,2.8264514451677147,313.71,48.42 +zephyr-7b-beta,afternoon,3.5789777278900146,277.6,44.016666666666666 +zephyr-7b-beta,early morning,3.937663261095683,273.03333333333336,43.45 +zephyr-7b-beta,evening,3.5673056403795878,273.3666666666667,43.5 +zephyr-7b-beta,late afternoon,3.4592524923459447,248.59,38.9 +zephyr-7b-beta,late evening,3.45343524068594,176.23125,27.21875 +zephyr-7b-beta,midnight,3.7253047794103624,217.82083333333333,33.67916666666667 +zephyr-7b-beta,morning,4.056525647640228,386.3,63.35 +zephyr-7b-beta,night,3.6954557319482166,216.55833333333334,33.46666666666667 diff --git a/data/2024-02-06 09:42:04.306128_time_of_day_comparison.csv b/data/2024-02-06 09:42:04.306128_time_of_day_comparison.csv new file mode 100644 index 0000000000000000000000000000000000000000..852b56a901f5d3b63a8b74ebbaf7b321fb14299e --- /dev/null +++ b/data/2024-02-06 09:42:04.306128_time_of_day_comparison.csv @@ -0,0 +1,89 @@ +model,time_of_day,execution_time,characters_count,words_count +Mistral-7B-Instruct-v0.2,0,1.9149879813194275,37.8,2.95 +Mistral-7B-Instruct-v0.2,3,3.734026002883911,362.9,58.35 +Mistral-7B-Instruct-v0.2,4,3.228973722457886,222.0625,32.25 +Mistral-7B-Instruct-v0.2,5,3.2048643112182615,219.8625,31.8 +Mistral-7B-Instruct-v0.2,6,3.397640073299408,261.18333333333334,40.1 +Mistral-7B-Instruct-v0.2,7,3.389284573495388,175.79375,25.68125 +Mixtral-8x7B-Instruct-v0.1,0,4.639010797279158,323.0394736842105,42.69210526315789 +Mixtral-8x7B-Instruct-v0.1,1,4.009439338194697,301.24545454545455,42.21818181818182 +Mixtral-8x7B-Instruct-v0.1,2,4.526968242530536,285.045,41.86 +Mixtral-8x7B-Instruct-v0.1,3,3.9661054956285575,304.82,47.28 +Mixtral-8x7B-Instruct-v0.1,4,5.362903979589355,369.3192307692308,54.353846153846156 +Mixtral-8x7B-Instruct-v0.1,5,5.80184749175942,347.9681818181818,47.27272727272727 +Mixtral-8x7B-Instruct-v0.1,6,3.6435119574237023,326.69,48.545 +Mixtral-8x7B-Instruct-v0.1,7,5.62397656769588,395.15714285714284,49.02857142857143 +TinyLlama/TinyLlama-1.1B-Chat-v1.0,0,1.6341248273849487,210.2,34.2 +TinyLlama/TinyLlama-1.1B-Chat-v1.0,1,2.0128010153770446,372.05,62.6 +TinyLlama/TinyLlama-1.1B-Chat-v1.0,2,2.0273348593711855,372.13,62.53 +TinyLlama/TinyLlama-1.1B-Chat-v1.0,3,1.9041210174560548,372.05,62.6 +TinyLlama/TinyLlama-1.1B-Chat-v1.0,4,1.8381905496120452,308.795,51.08 +TinyLlama/TinyLlama-1.1B-Chat-v1.0,5,1.7547113946505954,285.17857142857144,46.9 +TinyLlama/TinyLlama-1.1B-Chat-v1.0,6,1.7984187936782836,313.99,51.96 +TinyLlama/TinyLlama-1.1B-Chat-v1.0,7,1.5875422928068372,192.78333333333333,31.261111111111113 +chat-bison,0,3.890243631601334,398.075,49.0 +chat-bison (PaLM 2),0,2.468383938074112,381.95,60.9 +chat-bison (PaLM 2),1,2.460119960308075,381.92,60.94 +chat-bison (PaLM 2),2,2.4665334616388592,381.9214285714286,60.892857142857146 +chat-bison (PaLM 2),3,2.488477897644043,381.73,60.88 +chat-bison (PaLM 2),4,2.6460144804074215,376.28076923076924,55.965384615384615 +chat-bison (PaLM 2),5,3.0387172081253744,381.1363636363636,53.35454545454545 +chat-bison (PaLM 2),6,2.688272579908371,367.07,55.89 +chat-bison (PaLM 2),7,2.7250528037548065,382.725,52.95 +chat-bison-32k,0,4.128177767992019,389.925,48.025 +chat-bison-32k (PaLM 2 32K),0,7.7498266498247785,335.75,53.85 +chat-bison-32k (PaLM 2 32K),1,6.491292915344238,335.75,53.85 +chat-bison-32k (PaLM 2 32K),2,9.141417106560299,335.75,53.85 +chat-bison-32k (PaLM 2 32K),3,7.7035503840446475,335.75,53.85 +chat-bison-32k (PaLM 2 32K),4,5.014458654477046,339.3692307692308,49.323076923076925 +chat-bison-32k (PaLM 2 32K),5,4.5047362284226855,348.65909090909093,48.35454545454545 +chat-bison-32k (PaLM 2 32K),6,7.7332194912433625,329.46,49.5 +chat-bison-32k (PaLM 2 32K),7,7.796841062307358,349.95,47.805 +gemini-pro,0,3.338477972348531,369.825,55.9125 +gemini-pro,1,2.8375814715210272,374.8,60.04 +gemini-pro,2,2.7453590130460435,381.2214285714286,60.964285714285715 +gemini-pro,3,2.497767536007628,371.93,59.39 +gemini-pro,4,2.816922114008949,360.62307692307695,53.25769230769231 +gemini-pro,5,2.9268629640903114,364.57272727272726,50.1 +gemini-pro,6,2.86901999375759,366.4,55.045 +gemini-pro,7,3.7189874940246117,390.9142857142857,51.35 +gpt-3.5-turbo,0,3.822115447632102,426.71923076923076,49.05 +gpt-3.5-turbo,1,6.062970260473398,418.6192307692308,44.926923076923075 +gpt-3.5-turbo,2,3.787998208734724,403.74444444444447,47.34444444444444 +gpt-3.5-turbo,3,3.126271222697364,389.9888888888889,50.93888888888889 +gpt-3.5-turbo,4,3.9458200880459375,381.4428571428571,43.76190476190476 +gpt-3.5-turbo,5,4.384064777692159,396.4357142857143,43.28333333333333 +gpt-3.5-turbo,6,3.5153889304115657,385.18095238095236,46.01428571428571 +gpt-3.5-turbo,7,5.110168156187617,422.73510971786834,45.358934169278996 +gpt-4,0,12.3578163115329,334.075,41.35 +gpt-4,1,12.813134506115546,316.93461538461537,37.93076923076923 +gpt-4,2,14.348626694414351,323.5388888888889,40.544444444444444 +gpt-4,3,12.759107512468733,338.18333333333334,46.85 +gpt-4,4,16.002364798386893,318.3095238095238,38.77142857142857 +gpt-4,5,16.80607506932254,313.3595238095238,37.49285714285714 +gpt-4,6,13.841120740345547,318.0809523809524,40.19285714285714 +gpt-4,7,14.298642643005493,314.336,37.012 +gpt-4-turbo,0,13.770663784850727,382.7613636363636,47.61818181818182 +gpt-4-turbo,1,14.254795966698573,352.54615384615386,46.37692307692308 +gpt-4-turbo,2,11.555620827939775,357.65555555555557,47.21666666666667 +gpt-4-turbo,3,13.686854598257277,381.8888888888889,55.02777777777778 +gpt-4-turbo,4,13.997754749229976,351.01190476190476,46.03333333333333 +gpt-4-turbo,5,22.320911452883767,381.65714285714284,47.35476190476191 +gpt-4-turbo,6,16.550320884159632,382.31666666666666,48.45 +gpt-4-turbo,7,14.592236209392548,413.61,44.8 +llama-2-70b-chat,0,3.249819871626402,346.8875,52.06875 +llama-2-70b-chat,1,2.8264514451677147,313.71,48.42 +llama-2-70b-chat,2,2.8660141522424265,289.6642857142857,44.614285714285714 +llama-2-70b-chat,3,2.872361832027194,283.35,43.45 +llama-2-70b-chat,4,4.234376892130426,375.44615384615383,55.238461538461536 +llama-2-70b-chat,5,3.6833307104881365,433.6636363636364,59.445454545454545 +llama-2-70b-chat,6,2.9706250462084185,317.245,47.4 +llama-2-70b-chat,7,4.719581684340602,572.1689655172414,79.83103448275862 +zephyr-7b-beta,0,3.7253047794103624,217.82083333333333,33.67916666666667 +zephyr-7b-beta,1,3.6954557319482166,216.55833333333334,33.46666666666667 +zephyr-7b-beta,2,3.937663261095683,273.03333333333336,43.45 +zephyr-7b-beta,3,4.056525647640228,386.3,63.35 +zephyr-7b-beta,4,3.5789777278900146,277.6,44.016666666666666 +zephyr-7b-beta,5,3.4592524923459447,248.59,38.9 +zephyr-7b-beta,6,3.5673056403795878,273.3666666666667,43.5 +zephyr-7b-beta,7,3.45343524068594,176.23125,27.21875 diff --git a/data/2024-02-06 09:46:18.795794_time_of_day_comparison.csv b/data/2024-02-06 09:46:18.795794_time_of_day_comparison.csv new file mode 100644 index 0000000000000000000000000000000000000000..b84c62764a40b48049d275ce1f4b0bd23689e33c --- /dev/null +++ b/data/2024-02-06 09:46:18.795794_time_of_day_comparison.csv @@ -0,0 +1,89 @@ +model,time_of_day,execution_time,characters_count,words_count +Mistral-7B-Instruct-v0.2,midnight,1.9149879813194275,37.8,2.95 +Mistral-7B-Instruct-v0.2,morning,3.734026002883911,362.9,58.35 +Mistral-7B-Instruct-v0.2,afternoon,3.228973722457886,222.0625,32.25 +Mistral-7B-Instruct-v0.2,late afternoon,3.2048643112182615,219.8625,31.8 +Mistral-7B-Instruct-v0.2,evening,3.397640073299408,261.18333333333334,40.1 +Mistral-7B-Instruct-v0.2,late evening,3.389284573495388,175.79375,25.68125 +Mixtral-8x7B-Instruct-v0.1,midnight,4.639010797279158,323.0394736842105,42.69210526315789 +Mixtral-8x7B-Instruct-v0.1,night,4.009439338194697,301.24545454545455,42.21818181818182 +Mixtral-8x7B-Instruct-v0.1,early morning,4.526968242530536,285.045,41.86 +Mixtral-8x7B-Instruct-v0.1,morning,3.9661054956285575,304.82,47.28 +Mixtral-8x7B-Instruct-v0.1,afternoon,5.362903979589355,369.3192307692308,54.353846153846156 +Mixtral-8x7B-Instruct-v0.1,late afternoon,5.80184749175942,347.9681818181818,47.27272727272727 +Mixtral-8x7B-Instruct-v0.1,evening,3.6435119574237023,326.69,48.545 +Mixtral-8x7B-Instruct-v0.1,late evening,5.62397656769588,395.15714285714284,49.02857142857143 +TinyLlama/TinyLlama-1.1B-Chat-v1.0,midnight,1.6341248273849487,210.2,34.2 +TinyLlama/TinyLlama-1.1B-Chat-v1.0,night,2.0128010153770446,372.05,62.6 +TinyLlama/TinyLlama-1.1B-Chat-v1.0,early morning,2.0273348593711855,372.13,62.53 +TinyLlama/TinyLlama-1.1B-Chat-v1.0,morning,1.9041210174560548,372.05,62.6 +TinyLlama/TinyLlama-1.1B-Chat-v1.0,afternoon,1.8381905496120452,308.795,51.08 +TinyLlama/TinyLlama-1.1B-Chat-v1.0,late afternoon,1.7547113946505954,285.17857142857144,46.9 +TinyLlama/TinyLlama-1.1B-Chat-v1.0,evening,1.7984187936782836,313.99,51.96 +TinyLlama/TinyLlama-1.1B-Chat-v1.0,late evening,1.5875422928068372,192.78333333333333,31.261111111111113 +chat-bison,midnight,3.890243631601334,398.075,49.0 +chat-bison (PaLM 2),midnight,2.468383938074112,381.95,60.9 +chat-bison (PaLM 2),night,2.460119960308075,381.92,60.94 +chat-bison (PaLM 2),early morning,2.4665334616388592,381.9214285714286,60.892857142857146 +chat-bison (PaLM 2),morning,2.488477897644043,381.73,60.88 +chat-bison (PaLM 2),afternoon,2.6460144804074215,376.28076923076924,55.965384615384615 +chat-bison (PaLM 2),late afternoon,3.0387172081253744,381.1363636363636,53.35454545454545 +chat-bison (PaLM 2),evening,2.688272579908371,367.07,55.89 +chat-bison (PaLM 2),late evening,2.7250528037548065,382.725,52.95 +chat-bison-32k,midnight,4.128177767992019,389.925,48.025 +chat-bison-32k (PaLM 2 32K),midnight,7.7498266498247785,335.75,53.85 +chat-bison-32k (PaLM 2 32K),night,6.491292915344238,335.75,53.85 +chat-bison-32k (PaLM 2 32K),early morning,9.141417106560299,335.75,53.85 +chat-bison-32k (PaLM 2 32K),morning,7.7035503840446475,335.75,53.85 +chat-bison-32k (PaLM 2 32K),afternoon,5.014458654477046,339.3692307692308,49.323076923076925 +chat-bison-32k (PaLM 2 32K),late afternoon,4.5047362284226855,348.65909090909093,48.35454545454545 +chat-bison-32k (PaLM 2 32K),evening,7.7332194912433625,329.46,49.5 +chat-bison-32k (PaLM 2 32K),late evening,7.796841062307358,349.95,47.805 +gemini-pro,midnight,3.338477972348531,369.825,55.9125 +gemini-pro,night,2.8375814715210272,374.8,60.04 +gemini-pro,early morning,2.7453590130460435,381.2214285714286,60.964285714285715 +gemini-pro,morning,2.497767536007628,371.93,59.39 +gemini-pro,afternoon,2.816922114008949,360.62307692307695,53.25769230769231 +gemini-pro,late afternoon,2.9268629640903114,364.57272727272726,50.1 +gemini-pro,evening,2.86901999375759,366.4,55.045 +gemini-pro,late evening,3.7189874940246117,390.9142857142857,51.35 +gpt-3.5-turbo,midnight,3.822115447632102,426.71923076923076,49.05 +gpt-3.5-turbo,night,6.062970260473398,418.6192307692308,44.926923076923075 +gpt-3.5-turbo,early morning,3.787998208734724,403.74444444444447,47.34444444444444 +gpt-3.5-turbo,morning,3.126271222697364,389.9888888888889,50.93888888888889 +gpt-3.5-turbo,afternoon,3.9458200880459375,381.4428571428571,43.76190476190476 +gpt-3.5-turbo,late afternoon,4.384064777692159,396.4357142857143,43.28333333333333 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+gpt-4-turbo,afternoon,13.997754749229976,351.01190476190476,46.03333333333333 +gpt-4-turbo,late afternoon,22.320911452883767,381.65714285714284,47.35476190476191 +gpt-4-turbo,evening,16.550320884159632,382.31666666666666,48.45 +gpt-4-turbo,late evening,14.592236209392548,413.61,44.8 +llama-2-70b-chat,midnight,3.249819871626402,346.8875,52.06875 +llama-2-70b-chat,night,2.8264514451677147,313.71,48.42 +llama-2-70b-chat,early morning,2.8660141522424265,289.6642857142857,44.614285714285714 +llama-2-70b-chat,morning,2.872361832027194,283.35,43.45 +llama-2-70b-chat,afternoon,4.234376892130426,375.44615384615383,55.238461538461536 +llama-2-70b-chat,late afternoon,3.6833307104881365,433.6636363636364,59.445454545454545 +llama-2-70b-chat,evening,2.9706250462084185,317.245,47.4 +llama-2-70b-chat,late evening,4.719581684340602,572.1689655172414,79.83103448275862 +zephyr-7b-beta,midnight,3.7253047794103624,217.82083333333333,33.67916666666667 +zephyr-7b-beta,night,3.6954557319482166,216.55833333333334,33.46666666666667 +zephyr-7b-beta,early morning,3.937663261095683,273.03333333333336,43.45 +zephyr-7b-beta,morning,4.056525647640228,386.3,63.35 +zephyr-7b-beta,afternoon,3.5789777278900146,277.6,44.016666666666666 +zephyr-7b-beta,late afternoon,3.4592524923459447,248.59,38.9 +zephyr-7b-beta,evening,3.5673056403795878,273.3666666666667,43.5 +zephyr-7b-beta,late evening,3.45343524068594,176.23125,27.21875 diff --git a/data/2024-02-06 09:49:19.637072_time_of_day_comparison.csv b/data/2024-02-06 09:49:19.637072_time_of_day_comparison.csv new file mode 100644 index 0000000000000000000000000000000000000000..dff5a9f8560554f3431477e9b8550a8bd6a9e0a5 --- /dev/null +++ b/data/2024-02-06 09:49:19.637072_time_of_day_comparison.csv @@ -0,0 +1,89 @@ +model,time_of_day,execution_time,characters_count,words_count +Mistral-7B-Instruct-v0.2,morning,3.734026002883911,362.9,58.35 +Mistral-7B-Instruct-v0.2,afternoon,3.228973722457886,222.0625,32.25 +Mistral-7B-Instruct-v0.2,late afternoon,3.2048643112182615,219.8625,31.8 +Mistral-7B-Instruct-v0.2,evening,3.397640073299408,261.18333333333334,40.1 +Mistral-7B-Instruct-v0.2,late evening,3.389284573495388,175.79375,25.68125 +Mistral-7B-Instruct-v0.2,midnight,1.9149879813194275,37.8,2.95 +Mixtral-8x7B-Instruct-v0.1,early morning,4.526968242530536,285.045,41.86 +Mixtral-8x7B-Instruct-v0.1,morning,3.9661054956285575,304.82,47.28 +Mixtral-8x7B-Instruct-v0.1,afternoon,5.362903979589355,369.3192307692308,54.353846153846156 +Mixtral-8x7B-Instruct-v0.1,late afternoon,5.80184749175942,347.9681818181818,47.27272727272727 +Mixtral-8x7B-Instruct-v0.1,evening,3.6435119574237023,326.69,48.545 +Mixtral-8x7B-Instruct-v0.1,late evening,5.62397656769588,395.15714285714284,49.02857142857143 +Mixtral-8x7B-Instruct-v0.1,midnight,4.639010797279158,323.0394736842105,42.69210526315789 +Mixtral-8x7B-Instruct-v0.1,night,4.009439338194697,301.24545454545455,42.21818181818182 +TinyLlama/TinyLlama-1.1B-Chat-v1.0,early morning,2.0273348593711855,372.13,62.53 +TinyLlama/TinyLlama-1.1B-Chat-v1.0,morning,1.9041210174560548,372.05,62.6 +TinyLlama/TinyLlama-1.1B-Chat-v1.0,afternoon,1.8381905496120452,308.795,51.08 +TinyLlama/TinyLlama-1.1B-Chat-v1.0,late afternoon,1.7547113946505954,285.17857142857144,46.9 +TinyLlama/TinyLlama-1.1B-Chat-v1.0,evening,1.7984187936782836,313.99,51.96 +TinyLlama/TinyLlama-1.1B-Chat-v1.0,late evening,1.5875422928068372,192.78333333333333,31.261111111111113 +TinyLlama/TinyLlama-1.1B-Chat-v1.0,midnight,1.6341248273849487,210.2,34.2 +TinyLlama/TinyLlama-1.1B-Chat-v1.0,night,2.0128010153770446,372.05,62.6 +chat-bison,midnight,3.890243631601334,398.075,49.0 +chat-bison (PaLM 2),early morning,2.4665334616388592,381.9214285714286,60.892857142857146 +chat-bison (PaLM 2),morning,2.488477897644043,381.73,60.88 +chat-bison (PaLM 2),afternoon,2.6460144804074215,376.28076923076924,55.965384615384615 +chat-bison (PaLM 2),late afternoon,3.0387172081253744,381.1363636363636,53.35454545454545 +chat-bison (PaLM 2),evening,2.688272579908371,367.07,55.89 +chat-bison (PaLM 2),late evening,2.7250528037548065,382.725,52.95 +chat-bison (PaLM 2),midnight,2.468383938074112,381.95,60.9 +chat-bison (PaLM 2),night,2.460119960308075,381.92,60.94 +chat-bison-32k,midnight,4.128177767992019,389.925,48.025 +chat-bison-32k (PaLM 2 32K),early morning,9.141417106560299,335.75,53.85 +chat-bison-32k (PaLM 2 32K),morning,7.7035503840446475,335.75,53.85 +chat-bison-32k (PaLM 2 32K),afternoon,5.014458654477046,339.3692307692308,49.323076923076925 +chat-bison-32k (PaLM 2 32K),late afternoon,4.5047362284226855,348.65909090909093,48.35454545454545 +chat-bison-32k (PaLM 2 32K),evening,7.7332194912433625,329.46,49.5 +chat-bison-32k (PaLM 2 32K),late evening,7.796841062307358,349.95,47.805 +chat-bison-32k (PaLM 2 32K),midnight,7.7498266498247785,335.75,53.85 +chat-bison-32k (PaLM 2 32K),night,6.491292915344238,335.75,53.85 +gemini-pro,early morning,2.7453590130460435,381.2214285714286,60.964285714285715 +gemini-pro,morning,2.497767536007628,371.93,59.39 +gemini-pro,afternoon,2.816922114008949,360.62307692307695,53.25769230769231 +gemini-pro,late afternoon,2.9268629640903114,364.57272727272726,50.1 +gemini-pro,evening,2.86901999375759,366.4,55.045 +gemini-pro,late evening,3.7189874940246117,390.9142857142857,51.35 +gemini-pro,midnight,3.338477972348531,369.825,55.9125 +gemini-pro,night,2.8375814715210272,374.8,60.04 +gpt-3.5-turbo,early morning,3.787998208734724,403.74444444444447,47.34444444444444 +gpt-3.5-turbo,morning,3.126271222697364,389.9888888888889,50.93888888888889 +gpt-3.5-turbo,afternoon,3.9458200880459375,381.4428571428571,43.76190476190476 +gpt-3.5-turbo,late afternoon,4.384064777692159,396.4357142857143,43.28333333333333 +gpt-3.5-turbo,evening,3.5153889304115657,385.18095238095236,46.01428571428571 +gpt-3.5-turbo,late evening,5.110168156187617,422.73510971786834,45.358934169278996 +gpt-3.5-turbo,midnight,3.822115447632102,426.71923076923076,49.05 +gpt-3.5-turbo,night,6.062970260473398,418.6192307692308,44.926923076923075 +gpt-4,early morning,14.348626694414351,323.5388888888889,40.544444444444444 +gpt-4,morning,12.759107512468733,338.18333333333334,46.85 +gpt-4,afternoon,16.002364798386893,318.3095238095238,38.77142857142857 +gpt-4,late afternoon,16.80607506932254,313.3595238095238,37.49285714285714 +gpt-4,evening,13.841120740345547,318.0809523809524,40.19285714285714 +gpt-4,late evening,14.298642643005493,314.336,37.012 +gpt-4,midnight,12.3578163115329,334.075,41.35 +gpt-4,night,12.813134506115546,316.93461538461537,37.93076923076923 +gpt-4-turbo,early morning,11.555620827939775,357.65555555555557,47.21666666666667 +gpt-4-turbo,morning,13.686854598257277,381.8888888888889,55.02777777777778 +gpt-4-turbo,afternoon,13.997754749229976,351.01190476190476,46.03333333333333 +gpt-4-turbo,late afternoon,22.320911452883767,381.65714285714284,47.35476190476191 +gpt-4-turbo,evening,16.550320884159632,382.31666666666666,48.45 +gpt-4-turbo,late evening,14.592236209392548,413.61,44.8 +gpt-4-turbo,midnight,13.770663784850727,382.7613636363636,47.61818181818182 +gpt-4-turbo,night,14.254795966698573,352.54615384615386,46.37692307692308 +llama-2-70b-chat,early morning,2.8660141522424265,289.6642857142857,44.614285714285714 +llama-2-70b-chat,morning,2.872361832027194,283.35,43.45 +llama-2-70b-chat,afternoon,4.234376892130426,375.44615384615383,55.238461538461536 +llama-2-70b-chat,late afternoon,3.6833307104881365,433.6636363636364,59.445454545454545 +llama-2-70b-chat,evening,2.9706250462084185,317.245,47.4 +llama-2-70b-chat,late evening,4.719581684340602,572.1689655172414,79.83103448275862 +llama-2-70b-chat,midnight,3.249819871626402,346.8875,52.06875 +llama-2-70b-chat,night,2.8264514451677147,313.71,48.42 +zephyr-7b-beta,early morning,3.937663261095683,273.03333333333336,43.45 +zephyr-7b-beta,morning,4.056525647640228,386.3,63.35 +zephyr-7b-beta,afternoon,3.5789777278900146,277.6,44.016666666666666 +zephyr-7b-beta,late afternoon,3.4592524923459447,248.59,38.9 +zephyr-7b-beta,evening,3.5673056403795878,273.3666666666667,43.5 +zephyr-7b-beta,late evening,3.45343524068594,176.23125,27.21875 +zephyr-7b-beta,midnight,3.7253047794103624,217.82083333333333,33.67916666666667 +zephyr-7b-beta,night,3.6954557319482166,216.55833333333334,33.46666666666667 diff --git a/data/2024-02-06 13:25:55.133644_general_plot.csv b/data/2024-02-06 13:25:55.133644_general_plot.csv new file mode 100644 index 0000000000000000000000000000000000000000..637cefcfac1931a2e5a4f86ae321f0248d50bd95 --- /dev/null +++ b/data/2024-02-06 13:25:55.133644_general_plot.csv @@ -0,0 +1,284 @@ +path,plot_object,header,description,plot_json +./html/plots/response_times.html,"Figure({ + 'data': [{'alignmentgroup': 'True', + 'hovertemplate': 'Model=%{x}
Execution time (s)=%{y}', + 'legendgroup': 'Mistral-7B-Instruct-v0.2', + 'marker': {'color': '#636efa', 'pattern': {'shape': ''}}, + 'name': 'Mistral-7B-Instruct-v0.2', + 'offsetgroup': 'Mistral-7B-Instruct-v0.2', + 'orientation': 'v', + 'showlegend': True, + 'textposition': 'auto', + 'type': 'bar', + 'x': array(['Mistral-7B-Instruct-v0.2'], dtype=object), + 'xaxis': 'x', + 'y': array([3.27102681]), + 'yaxis': 'y'}, + {'alignmentgroup': 'True', + 'hovertemplate': 'Model=%{x}
Execution time (s)=%{y}', + 'legendgroup': 'Mixtral-8x7B-Instruct-v0.1', + 'marker': {'color': '#EF553B', 'pattern': {'shape': ''}}, + 'name': 'Mixtral-8x7B-Instruct-v0.1', + 'offsetgroup': 'Mixtral-8x7B-Instruct-v0.1', + 'orientation': 'v', + 'showlegend': True, + 'textposition': 'auto', + 'type': 'bar', + 'x': array(['Mixtral-8x7B-Instruct-v0.1'], dtype=object), + 'xaxis': 'x', + 'y': array([4.83500647]), + 'yaxis': 'y'}, + {'alignmentgroup': 'True', + 'hovertemplate': 'Model=%{x}
Execution time (s)=%{y}', + 'legendgroup': 'TinyLlama/TinyLlama-1.1B-Chat-v1.0', + 'marker': {'color': '#00cc96', 'pattern': {'shape': ''}}, + 'name': 'TinyLlama/TinyLlama-1.1B-Chat-v1.0', + 'offsetgroup': 'TinyLlama/TinyLlama-1.1B-Chat-v1.0', + 'orientation': 'v', + 'showlegend': True, + 'textposition': 'auto', + 'type': 'bar', + 'x': array(['TinyLlama/TinyLlama-1.1B-Chat-v1.0'], dtype=object), + 'xaxis': 'x', + 'y': array([1.79273835]), + 'yaxis': 'y'}, + {'alignmentgroup': 'True', + 'hovertemplate': 'Model=%{x}
Execution time (s)=%{y}', + 'legendgroup': 'chat-bison', + 'marker': {'color': '#ab63fa', 'pattern': {'shape': ''}}, + 'name': 'chat-bison', + 'offsetgroup': 'chat-bison', + 'orientation': 'v', + 'showlegend': True, + 'textposition': 'auto', + 'type': 'bar', + 'x': array(['chat-bison'], dtype=object), + 'xaxis': 'x', + 'y': array([3.89024363]), + 'yaxis': 'y'}, + {'alignmentgroup': 'True', + 'hovertemplate': 'Model=%{x}
Execution time (s)=%{y}', + 'legendgroup': 'chat-bison (PaLM 2)', + 'marker': {'color': '#FFA15A', 'pattern': {'shape': ''}}, + 'name': 'chat-bison (PaLM 2)', + 'offsetgroup': 'chat-bison (PaLM 2)', + 'orientation': 'v', + 'showlegend': True, + 'textposition': 'auto', + 'type': 'bar', + 'x': array(['chat-bison (PaLM 2)'], dtype=object), + 'xaxis': 'x', + 'y': array([2.66830386]), + 'yaxis': 'y'}, + {'alignmentgroup': 'True', + 'hovertemplate': 'Model=%{x}
Execution time (s)=%{y}', + 'legendgroup': 'chat-bison-32k', + 'marker': {'color': '#19d3f3', 'pattern': {'shape': ''}}, + 'name': 'chat-bison-32k', + 'offsetgroup': 'chat-bison-32k', + 'orientation': 'v', + 'showlegend': True, + 'textposition': 'auto', + 'type': 'bar', + 'x': array(['chat-bison-32k'], dtype=object), + 'xaxis': 'x', + 'y': array([4.12817777]), + 'yaxis': 'y'}, + {'alignmentgroup': 'True', + 'hovertemplate': 'Model=%{x}
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Execution time (s)=%{y}', + 'legendgroup': 'zephyr-7b-beta', + 'marker': {'color': '#00cc96', 'pattern': {'shape': ''}}, + 'name': 'zephyr-7b-beta', + 'offsetgroup': 'zephyr-7b-beta', + 'orientation': 'v', + 'showlegend': True, + 'textposition': 'auto', + 'type': 'bar', + 'x': array(['zephyr-7b-beta'], dtype=object), + 'xaxis': 'x', + 'y': array([3.6370095]), + 'yaxis': 'y'}], + 'layout': {'barmode': 'relative', + 'legend': {'title': {'text': 'Model'}, 'tracegroupgap': 0}, + 'template': '...', + 'title': {'text': 'Model endpoints response times'}, + 'xaxis': {'anchor': 'y', + 'categoryarray': [Mistral-7B-Instruct-v0.2, + Mixtral-8x7B-Instruct-v0.1, + TinyLlama/TinyLlama-1.1B-Chat-v1.0, + chat-bison, chat-bison (PaLM 2), chat- + bison-32k, chat-bison-32k (PaLM 2 32K), + gemini-pro, gpt-3.5-turbo, gpt-4, + gpt-4-turbo, llama-2-70b-chat, + zephyr-7b-beta], + 'categoryorder': 'array', + 'domain': [0.0, 1.0], + 'title': {'text': 'Model'}}, + 'yaxis': {'anchor': 'x', 'domain': [0.0, 1.0], 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+Mistral-7B-Instruct-v0.2,afternoon,3.228973722457886,222.0625,32.25,Hugging Face Inference Endpoint +Mistral-7B-Instruct-v0.2,late afternoon,3.2048643112182615,219.8625,31.8,Hugging Face Inference Endpoint +Mistral-7B-Instruct-v0.2,evening,3.397640073299408,261.18333333333334,40.1,Hugging Face Inference Endpoint +Mistral-7B-Instruct-v0.2,late evening,3.389284573495388,175.79375,25.68125,Hugging Face Inference Endpoint +Mistral-7B-Instruct-v0.2,midnight,1.9149879813194275,37.8,2.95,Hugging Face Inference Endpoint +Mixtral-8x7B-Instruct-v0.1,early morning,4.526968242530536,285.045,41.86,Together AI +Mixtral-8x7B-Instruct-v0.1,morning,3.9661054956285575,304.82,47.28,Together AI +Mixtral-8x7B-Instruct-v0.1,afternoon,5.362903979589355,369.3192307692308,54.353846153846156,Together AI +Mixtral-8x7B-Instruct-v0.1,late afternoon,5.80184749175942,347.9681818181818,47.27272727272727,Together AI +Mixtral-8x7B-Instruct-v0.1,evening,3.6435119574237023,326.69,48.545,Together AI 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Inference Endpoint +TinyLlama/TinyLlama-1.1B-Chat-v1.0,midnight,1.6341248273849487,210.2,34.2,Hugging Face Inference Endpoint +TinyLlama/TinyLlama-1.1B-Chat-v1.0,night,2.0128010153770446,372.05,62.6,Hugging Face Inference Endpoint +chat-bison (PaLM 2),early morning,2.4665334616388592,381.9214285714286,60.892857142857146,Google VertexAI +chat-bison (PaLM 2),morning,2.488477897644043,381.73,60.88,Google VertexAI +chat-bison (PaLM 2),afternoon,2.6460144804074215,376.28076923076924,55.965384615384615,Google VertexAI +chat-bison (PaLM 2),late afternoon,3.0387172081253744,381.1363636363636,53.35454545454545,Google VertexAI +chat-bison (PaLM 2),evening,2.688272579908371,367.07,55.89,Google VertexAI +chat-bison (PaLM 2),late evening,2.7250528037548065,382.725,52.95,Google VertexAI +chat-bison (PaLM 2),midnight,2.468383938074112,381.95,60.9,Google VertexAI +chat-bison (PaLM 2),night,2.460119960308075,381.92,60.94,Google VertexAI +chat-bison-32k (PaLM 2 32K),early morning,9.141417106560299,335.75,53.85,Google VertexAI +chat-bison-32k (PaLM 2 32K),morning,7.7035503840446475,335.75,53.85,Google VertexAI +chat-bison-32k (PaLM 2 32K),afternoon,5.014458654477046,339.3692307692308,49.323076923076925,Google VertexAI +chat-bison-32k (PaLM 2 32K),late afternoon,4.5047362284226855,348.65909090909093,48.35454545454545,Google VertexAI +chat-bison-32k (PaLM 2 32K),evening,7.7332194912433625,329.46,49.5,Google VertexAI +chat-bison-32k (PaLM 2 32K),late evening,7.796841062307358,349.95,47.805,Google VertexAI +chat-bison-32k (PaLM 2 32K),midnight,7.7498266498247785,335.75,53.85,Google VertexAI +chat-bison-32k (PaLM 2 32K),night,6.491292915344238,335.75,53.85,Google VertexAI +gemini-pro,early morning,2.7453590130460435,381.2214285714286,60.964285714285715,Google VertexAI +gemini-pro,morning,2.497767536007628,371.93,59.39,Google VertexAI +gemini-pro,afternoon,2.816922114008949,360.62307692307695,53.25769230769231,Google VertexAI +gemini-pro,late 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afternoon,22.320911452883767,381.65714285714284,47.35476190476191,OpenAI +gpt-4-turbo,evening,16.550320884159632,382.31666666666666,48.45,OpenAI +gpt-4-turbo,late evening,14.592236209392548,413.61,44.8,OpenAI +gpt-4-turbo,midnight,13.770663784850727,382.7613636363636,47.61818181818182,OpenAI +gpt-4-turbo,night,14.254795966698573,352.54615384615386,46.37692307692308,OpenAI +llama-2-70b-chat,early morning,2.8660141522424265,289.6642857142857,44.614285714285714,Together AI +llama-2-70b-chat,morning,2.872361832027194,283.35,43.45,Together AI +llama-2-70b-chat,afternoon,4.234376892130426,375.44615384615383,55.238461538461536,Together AI +llama-2-70b-chat,late afternoon,3.6833307104881365,433.6636363636364,59.445454545454545,Together AI +llama-2-70b-chat,evening,2.9706250462084185,317.245,47.4,Together AI +llama-2-70b-chat,late evening,4.719581684340602,572.1689655172414,79.83103448275862,Together AI +llama-2-70b-chat,midnight,3.249819871626402,346.8875,52.06875,Together AI +llama-2-70b-chat,night,2.8264514451677147,313.71,48.42,Together AI +zephyr-7b-beta,early morning,3.937663261095683,273.03333333333336,43.45,Hugging Face Inference Endpoint +zephyr-7b-beta,morning,4.056525647640228,386.3,63.35,Hugging Face Inference Endpoint +zephyr-7b-beta,afternoon,3.5789777278900146,277.6,44.016666666666666,Hugging Face Inference Endpoint +zephyr-7b-beta,late afternoon,3.4592524923459447,248.59,38.9,Hugging Face Inference Endpoint +zephyr-7b-beta,evening,3.5673056403795878,273.3666666666667,43.5,Hugging Face Inference Endpoint +zephyr-7b-beta,late evening,3.45343524068594,176.23125,27.21875,Hugging Face Inference Endpoint +zephyr-7b-beta,midnight,3.7253047794103624,217.82083333333333,33.67916666666667,Hugging Face Inference Endpoint +zephyr-7b-beta,night,3.6954557319482166,216.55833333333334,33.46666666666667,Hugging Face Inference Endpoint diff --git a/data/2024-02-08 14:18:58.194844_time_of_day_comparison.csv b/data/2024-02-08 14:18:58.194844_time_of_day_comparison.csv new file mode 100644 index 0000000000000000000000000000000000000000..b6cbe6f05c06fe1e841931962a75943878678a8c --- /dev/null +++ b/data/2024-02-08 14:18:58.194844_time_of_day_comparison.csv @@ -0,0 +1,87 @@ +model,time_of_day,execution_time,characters_count,words_count,provider +Mistral-7B-Instruct-v0.2,morning,3.734026002883911,362.9,58.35,Hugging Face Inference Endpoint +Mistral-7B-Instruct-v0.2,afternoon,3.228973722457886,222.0625,32.25,Hugging Face Inference Endpoint +Mistral-7B-Instruct-v0.2,late afternoon,3.2048643112182615,219.8625,31.8,Hugging Face Inference Endpoint +Mistral-7B-Instruct-v0.2,evening,3.397640073299408,261.18333333333334,40.1,Hugging Face Inference Endpoint +Mistral-7B-Instruct-v0.2,late evening,3.389284573495388,175.79375,25.68125,Hugging Face Inference Endpoint +Mistral-7B-Instruct-v0.2,midnight,1.9149879813194275,37.8,2.95,Hugging Face Inference Endpoint +Mixtral-8x7B-Instruct-v0.1,early morning,4.526968242530536,285.045,41.86,Together AI +Mixtral-8x7B-Instruct-v0.1,morning,3.9661054956285575,304.82,47.28,Together AI +Mixtral-8x7B-Instruct-v0.1,afternoon,5.362903979589355,369.3192307692308,54.353846153846156,Together AI +Mixtral-8x7B-Instruct-v0.1,late afternoon,5.80184749175942,347.9681818181818,47.27272727272727,Together AI +Mixtral-8x7B-Instruct-v0.1,evening,3.6435119574237023,326.69,48.545,Together AI +Mixtral-8x7B-Instruct-v0.1,late evening,5.62397656769588,395.15714285714284,49.02857142857143,Together AI +Mixtral-8x7B-Instruct-v0.1,midnight,4.639010797279158,323.0394736842105,42.69210526315789,Together AI +Mixtral-8x7B-Instruct-v0.1,night,4.009439338194697,301.24545454545455,42.21818181818182,Together AI +TinyLlama/TinyLlama-1.1B-Chat-v1.0,early morning,2.0273348593711855,372.13,62.53,Hugging Face Inference Endpoint +TinyLlama/TinyLlama-1.1B-Chat-v1.0,morning,1.9041210174560548,372.05,62.6,Hugging Face Inference Endpoint +TinyLlama/TinyLlama-1.1B-Chat-v1.0,afternoon,1.8381905496120452,308.795,51.08,Hugging Face Inference Endpoint +TinyLlama/TinyLlama-1.1B-Chat-v1.0,late afternoon,1.7547113946505954,285.17857142857144,46.9,Hugging Face Inference Endpoint +TinyLlama/TinyLlama-1.1B-Chat-v1.0,evening,1.7984187936782836,313.99,51.96,Hugging Face Inference Endpoint +TinyLlama/TinyLlama-1.1B-Chat-v1.0,late evening,1.5875422928068372,192.78333333333333,31.261111111111113,Hugging Face Inference Endpoint +TinyLlama/TinyLlama-1.1B-Chat-v1.0,midnight,1.6341248273849487,210.2,34.2,Hugging Face Inference Endpoint +TinyLlama/TinyLlama-1.1B-Chat-v1.0,night,2.0128010153770446,372.05,62.6,Hugging Face Inference Endpoint +chat-bison (PaLM 2),early morning,2.4665334616388592,381.9214285714286,60.892857142857146,Google VertexAI +chat-bison (PaLM 2),morning,2.488477897644043,381.73,60.88,Google VertexAI +chat-bison (PaLM 2),afternoon,2.6460144804074215,376.28076923076924,55.965384615384615,Google VertexAI +chat-bison (PaLM 2),late afternoon,3.0387172081253744,381.1363636363636,53.35454545454545,Google VertexAI +chat-bison (PaLM 2),evening,2.688272579908371,367.07,55.89,Google VertexAI +chat-bison (PaLM 2),late evening,2.7250528037548065,382.725,52.95,Google VertexAI +chat-bison (PaLM 2),midnight,2.468383938074112,381.95,60.9,Google VertexAI +chat-bison (PaLM 2),night,2.460119960308075,381.92,60.94,Google VertexAI +chat-bison-32k (PaLM 2 32K),early morning,9.141417106560299,335.75,53.85,Google VertexAI +chat-bison-32k (PaLM 2 32K),morning,7.7035503840446475,335.75,53.85,Google VertexAI +chat-bison-32k (PaLM 2 32K),afternoon,5.014458654477046,339.3692307692308,49.323076923076925,Google VertexAI +chat-bison-32k (PaLM 2 32K),late afternoon,4.5047362284226855,348.65909090909093,48.35454545454545,Google VertexAI +chat-bison-32k (PaLM 2 32K),evening,7.7332194912433625,329.46,49.5,Google VertexAI +chat-bison-32k (PaLM 2 32K),late evening,7.796841062307358,349.95,47.805,Google VertexAI +chat-bison-32k (PaLM 2 32K),midnight,7.7498266498247785,335.75,53.85,Google VertexAI +chat-bison-32k (PaLM 2 32K),night,6.491292915344238,335.75,53.85,Google VertexAI +gemini-pro,early morning,2.7453590130460435,381.2214285714286,60.964285714285715,Google VertexAI +gemini-pro,morning,2.497767536007628,371.93,59.39,Google VertexAI +gemini-pro,afternoon,2.816922114008949,360.62307692307695,53.25769230769231,Google VertexAI +gemini-pro,late afternoon,2.9268629640903114,364.57272727272726,50.1,Google VertexAI +gemini-pro,evening,2.86901999375759,366.4,55.045,Google VertexAI +gemini-pro,late evening,3.7189874940246117,390.9142857142857,51.35,Google VertexAI +gemini-pro,midnight,3.338477972348531,369.825,55.9125,Google VertexAI +gemini-pro,night,2.8375814715210272,374.8,60.04,Google VertexAI +gpt-3.5-turbo,early morning,3.787998208734724,403.74444444444447,47.34444444444444,OpenAI +gpt-3.5-turbo,morning,3.126271222697364,389.9888888888889,50.93888888888889,OpenAI +gpt-3.5-turbo,afternoon,3.9458200880459375,381.4428571428571,43.76190476190476,OpenAI +gpt-3.5-turbo,late afternoon,4.384064777692159,396.4357142857143,43.28333333333333,OpenAI +gpt-3.5-turbo,evening,3.5153889304115657,385.18095238095236,46.01428571428571,OpenAI +gpt-3.5-turbo,late evening,5.110168156187617,422.73510971786834,45.358934169278996,OpenAI +gpt-3.5-turbo,midnight,3.822115447632102,426.71923076923076,49.05,OpenAI +gpt-3.5-turbo,night,6.062970260473398,418.6192307692308,44.926923076923075,OpenAI +gpt-4,early morning,14.348626694414351,323.5388888888889,40.544444444444444,OpenAI +gpt-4,morning,12.759107512468733,338.18333333333334,46.85,OpenAI +gpt-4,afternoon,16.002364798386893,318.3095238095238,38.77142857142857,OpenAI +gpt-4,late afternoon,16.80607506932254,313.3595238095238,37.49285714285714,OpenAI +gpt-4,evening,13.841120740345547,318.0809523809524,40.19285714285714,OpenAI +gpt-4,late evening,14.298642643005493,314.336,37.012,OpenAI +gpt-4,midnight,12.3578163115329,334.075,41.35,OpenAI +gpt-4,night,12.813134506115546,316.93461538461537,37.93076923076923,OpenAI +gpt-4-turbo,early morning,11.555620827939775,357.65555555555557,47.21666666666667,OpenAI +gpt-4-turbo,morning,13.686854598257277,381.8888888888889,55.02777777777778,OpenAI +gpt-4-turbo,afternoon,13.997754749229976,351.01190476190476,46.03333333333333,OpenAI +gpt-4-turbo,late afternoon,22.320911452883767,381.65714285714284,47.35476190476191,OpenAI +gpt-4-turbo,evening,16.550320884159632,382.31666666666666,48.45,OpenAI +gpt-4-turbo,late evening,14.592236209392548,413.61,44.8,OpenAI +gpt-4-turbo,midnight,13.770663784850727,382.7613636363636,47.61818181818182,OpenAI +gpt-4-turbo,night,14.254795966698573,352.54615384615386,46.37692307692308,OpenAI +llama-2-70b-chat,early morning,2.8660141522424265,289.6642857142857,44.614285714285714,Together AI +llama-2-70b-chat,morning,2.872361832027194,283.35,43.45,Together AI +llama-2-70b-chat,afternoon,4.234376892130426,375.44615384615383,55.238461538461536,Together AI +llama-2-70b-chat,late afternoon,3.6833307104881365,433.6636363636364,59.445454545454545,Together AI +llama-2-70b-chat,evening,2.9706250462084185,317.245,47.4,Together AI +llama-2-70b-chat,late evening,4.719581684340602,572.1689655172414,79.83103448275862,Together AI +llama-2-70b-chat,midnight,3.249819871626402,346.8875,52.06875,Together AI +llama-2-70b-chat,night,2.8264514451677147,313.71,48.42,Together AI +zephyr-7b-beta,early morning,3.937663261095683,273.03333333333336,43.45,Hugging Face Inference Endpoint +zephyr-7b-beta,morning,4.056525647640228,386.3,63.35,Hugging Face Inference Endpoint +zephyr-7b-beta,afternoon,3.5789777278900146,277.6,44.016666666666666,Hugging Face Inference Endpoint +zephyr-7b-beta,late afternoon,3.4592524923459447,248.59,38.9,Hugging Face Inference Endpoint +zephyr-7b-beta,evening,3.5673056403795878,273.3666666666667,43.5,Hugging Face Inference Endpoint +zephyr-7b-beta,late evening,3.45343524068594,176.23125,27.21875,Hugging Face Inference Endpoint +zephyr-7b-beta,midnight,3.7253047794103624,217.82083333333333,33.67916666666667,Hugging Face Inference Endpoint +zephyr-7b-beta,night,3.6954557319482166,216.55833333333334,33.46666666666667,Hugging Face Inference Endpoint diff --git a/data/2024-02-08 14:20:56.432044_time_of_day_comparison.csv b/data/2024-02-08 14:20:56.432044_time_of_day_comparison.csv new file mode 100644 index 0000000000000000000000000000000000000000..9faef930e644066a103bfb8de4f072f380b28fd9 --- /dev/null +++ b/data/2024-02-08 14:20:56.432044_time_of_day_comparison.csv @@ -0,0 +1,87 @@ +provider,model,time_of_day,execution_time,characters_count,words_count +Mistral-7B-Instruct-v0.2,morning,3.734026002883911,362.9,58.35,Hugging Face Inference Endpoint +Mistral-7B-Instruct-v0.2,afternoon,3.228973722457886,222.0625,32.25,Hugging Face Inference Endpoint +Mistral-7B-Instruct-v0.2,late afternoon,3.2048643112182615,219.8625,31.8,Hugging Face Inference Endpoint +Mistral-7B-Instruct-v0.2,evening,3.397640073299408,261.18333333333334,40.1,Hugging Face Inference Endpoint +Mistral-7B-Instruct-v0.2,late evening,3.389284573495388,175.79375,25.68125,Hugging Face Inference Endpoint +Mistral-7B-Instruct-v0.2,midnight,1.9149879813194275,37.8,2.95,Hugging Face Inference Endpoint +Mixtral-8x7B-Instruct-v0.1,early morning,4.526968242530536,285.045,41.86,Together AI +Mixtral-8x7B-Instruct-v0.1,morning,3.9661054956285575,304.82,47.28,Together AI +Mixtral-8x7B-Instruct-v0.1,afternoon,5.362903979589355,369.3192307692308,54.353846153846156,Together AI +Mixtral-8x7B-Instruct-v0.1,late afternoon,5.80184749175942,347.9681818181818,47.27272727272727,Together AI +Mixtral-8x7B-Instruct-v0.1,evening,3.6435119574237023,326.69,48.545,Together AI +Mixtral-8x7B-Instruct-v0.1,late evening,5.62397656769588,395.15714285714284,49.02857142857143,Together AI +Mixtral-8x7B-Instruct-v0.1,midnight,4.639010797279158,323.0394736842105,42.69210526315789,Together AI +Mixtral-8x7B-Instruct-v0.1,night,4.009439338194697,301.24545454545455,42.21818181818182,Together AI +TinyLlama/TinyLlama-1.1B-Chat-v1.0,early morning,2.0273348593711855,372.13,62.53,Hugging Face Inference Endpoint +TinyLlama/TinyLlama-1.1B-Chat-v1.0,morning,1.9041210174560548,372.05,62.6,Hugging Face Inference Endpoint +TinyLlama/TinyLlama-1.1B-Chat-v1.0,afternoon,1.8381905496120452,308.795,51.08,Hugging Face Inference Endpoint +TinyLlama/TinyLlama-1.1B-Chat-v1.0,late afternoon,1.7547113946505954,285.17857142857144,46.9,Hugging Face Inference Endpoint +TinyLlama/TinyLlama-1.1B-Chat-v1.0,evening,1.7984187936782836,313.99,51.96,Hugging Face Inference Endpoint +TinyLlama/TinyLlama-1.1B-Chat-v1.0,late evening,1.5875422928068372,192.78333333333333,31.261111111111113,Hugging Face Inference Endpoint +TinyLlama/TinyLlama-1.1B-Chat-v1.0,midnight,1.6341248273849487,210.2,34.2,Hugging Face Inference Endpoint +TinyLlama/TinyLlama-1.1B-Chat-v1.0,night,2.0128010153770446,372.05,62.6,Hugging Face Inference Endpoint +chat-bison (PaLM 2),early morning,2.4665334616388592,381.9214285714286,60.892857142857146,Google VertexAI +chat-bison (PaLM 2),morning,2.488477897644043,381.73,60.88,Google VertexAI +chat-bison (PaLM 2),afternoon,2.6460144804074215,376.28076923076924,55.965384615384615,Google VertexAI +chat-bison (PaLM 2),late afternoon,3.0387172081253744,381.1363636363636,53.35454545454545,Google VertexAI +chat-bison (PaLM 2),evening,2.688272579908371,367.07,55.89,Google VertexAI +chat-bison (PaLM 2),late evening,2.7250528037548065,382.725,52.95,Google VertexAI +chat-bison (PaLM 2),midnight,2.468383938074112,381.95,60.9,Google VertexAI +chat-bison (PaLM 2),night,2.460119960308075,381.92,60.94,Google VertexAI +chat-bison-32k (PaLM 2 32K),early morning,9.141417106560299,335.75,53.85,Google VertexAI +chat-bison-32k (PaLM 2 32K),morning,7.7035503840446475,335.75,53.85,Google VertexAI +chat-bison-32k (PaLM 2 32K),afternoon,5.014458654477046,339.3692307692308,49.323076923076925,Google VertexAI +chat-bison-32k (PaLM 2 32K),late afternoon,4.5047362284226855,348.65909090909093,48.35454545454545,Google VertexAI +chat-bison-32k (PaLM 2 32K),evening,7.7332194912433625,329.46,49.5,Google VertexAI +chat-bison-32k (PaLM 2 32K),late evening,7.796841062307358,349.95,47.805,Google VertexAI +chat-bison-32k (PaLM 2 32K),midnight,7.7498266498247785,335.75,53.85,Google VertexAI +chat-bison-32k (PaLM 2 32K),night,6.491292915344238,335.75,53.85,Google VertexAI +gemini-pro,early morning,2.7453590130460435,381.2214285714286,60.964285714285715,Google VertexAI +gemini-pro,morning,2.497767536007628,371.93,59.39,Google VertexAI +gemini-pro,afternoon,2.816922114008949,360.62307692307695,53.25769230769231,Google VertexAI +gemini-pro,late afternoon,2.9268629640903114,364.57272727272726,50.1,Google VertexAI +gemini-pro,evening,2.86901999375759,366.4,55.045,Google VertexAI +gemini-pro,late evening,3.7189874940246117,390.9142857142857,51.35,Google VertexAI +gemini-pro,midnight,3.338477972348531,369.825,55.9125,Google VertexAI +gemini-pro,night,2.8375814715210272,374.8,60.04,Google VertexAI +gpt-3.5-turbo,early morning,3.787998208734724,403.74444444444447,47.34444444444444,OpenAI +gpt-3.5-turbo,morning,3.126271222697364,389.9888888888889,50.93888888888889,OpenAI +gpt-3.5-turbo,afternoon,3.9458200880459375,381.4428571428571,43.76190476190476,OpenAI +gpt-3.5-turbo,late afternoon,4.384064777692159,396.4357142857143,43.28333333333333,OpenAI +gpt-3.5-turbo,evening,3.5153889304115657,385.18095238095236,46.01428571428571,OpenAI +gpt-3.5-turbo,late evening,5.110168156187617,422.73510971786834,45.358934169278996,OpenAI +gpt-3.5-turbo,midnight,3.822115447632102,426.71923076923076,49.05,OpenAI +gpt-3.5-turbo,night,6.062970260473398,418.6192307692308,44.926923076923075,OpenAI +gpt-4,early morning,14.348626694414351,323.5388888888889,40.544444444444444,OpenAI +gpt-4,morning,12.759107512468733,338.18333333333334,46.85,OpenAI +gpt-4,afternoon,16.002364798386893,318.3095238095238,38.77142857142857,OpenAI +gpt-4,late afternoon,16.80607506932254,313.3595238095238,37.49285714285714,OpenAI +gpt-4,evening,13.841120740345547,318.0809523809524,40.19285714285714,OpenAI +gpt-4,late evening,14.298642643005493,314.336,37.012,OpenAI +gpt-4,midnight,12.3578163115329,334.075,41.35,OpenAI +gpt-4,night,12.813134506115546,316.93461538461537,37.93076923076923,OpenAI +gpt-4-turbo,early morning,11.555620827939775,357.65555555555557,47.21666666666667,OpenAI +gpt-4-turbo,morning,13.686854598257277,381.8888888888889,55.02777777777778,OpenAI +gpt-4-turbo,afternoon,13.997754749229976,351.01190476190476,46.03333333333333,OpenAI +gpt-4-turbo,late afternoon,22.320911452883767,381.65714285714284,47.35476190476191,OpenAI +gpt-4-turbo,evening,16.550320884159632,382.31666666666666,48.45,OpenAI +gpt-4-turbo,late evening,14.592236209392548,413.61,44.8,OpenAI +gpt-4-turbo,midnight,13.770663784850727,382.7613636363636,47.61818181818182,OpenAI +gpt-4-turbo,night,14.254795966698573,352.54615384615386,46.37692307692308,OpenAI +llama-2-70b-chat,early morning,2.8660141522424265,289.6642857142857,44.614285714285714,Together AI +llama-2-70b-chat,morning,2.872361832027194,283.35,43.45,Together AI +llama-2-70b-chat,afternoon,4.234376892130426,375.44615384615383,55.238461538461536,Together AI +llama-2-70b-chat,late afternoon,3.6833307104881365,433.6636363636364,59.445454545454545,Together AI +llama-2-70b-chat,evening,2.9706250462084185,317.245,47.4,Together AI +llama-2-70b-chat,late evening,4.719581684340602,572.1689655172414,79.83103448275862,Together AI +llama-2-70b-chat,midnight,3.249819871626402,346.8875,52.06875,Together AI +llama-2-70b-chat,night,2.8264514451677147,313.71,48.42,Together AI +zephyr-7b-beta,early morning,3.937663261095683,273.03333333333336,43.45,Hugging Face Inference Endpoint +zephyr-7b-beta,morning,4.056525647640228,386.3,63.35,Hugging Face Inference Endpoint +zephyr-7b-beta,afternoon,3.5789777278900146,277.6,44.016666666666666,Hugging Face Inference Endpoint +zephyr-7b-beta,late afternoon,3.4592524923459447,248.59,38.9,Hugging Face Inference Endpoint +zephyr-7b-beta,evening,3.5673056403795878,273.3666666666667,43.5,Hugging Face Inference Endpoint +zephyr-7b-beta,late evening,3.45343524068594,176.23125,27.21875,Hugging Face Inference Endpoint +zephyr-7b-beta,midnight,3.7253047794103624,217.82083333333333,33.67916666666667,Hugging Face Inference Endpoint +zephyr-7b-beta,night,3.6954557319482166,216.55833333333334,33.46666666666667,Hugging Face Inference Endpoint diff --git a/data/2024-02-08 14:22:42.700060_time_of_day_comparison.csv b/data/2024-02-08 14:22:42.700060_time_of_day_comparison.csv new file mode 100644 index 0000000000000000000000000000000000000000..dff5a9f8560554f3431477e9b8550a8bd6a9e0a5 --- /dev/null +++ b/data/2024-02-08 14:22:42.700060_time_of_day_comparison.csv @@ -0,0 +1,89 @@ +model,time_of_day,execution_time,characters_count,words_count +Mistral-7B-Instruct-v0.2,morning,3.734026002883911,362.9,58.35 +Mistral-7B-Instruct-v0.2,afternoon,3.228973722457886,222.0625,32.25 +Mistral-7B-Instruct-v0.2,late afternoon,3.2048643112182615,219.8625,31.8 +Mistral-7B-Instruct-v0.2,evening,3.397640073299408,261.18333333333334,40.1 +Mistral-7B-Instruct-v0.2,late evening,3.389284573495388,175.79375,25.68125 +Mistral-7B-Instruct-v0.2,midnight,1.9149879813194275,37.8,2.95 +Mixtral-8x7B-Instruct-v0.1,early morning,4.526968242530536,285.045,41.86 +Mixtral-8x7B-Instruct-v0.1,morning,3.9661054956285575,304.82,47.28 +Mixtral-8x7B-Instruct-v0.1,afternoon,5.362903979589355,369.3192307692308,54.353846153846156 +Mixtral-8x7B-Instruct-v0.1,late afternoon,5.80184749175942,347.9681818181818,47.27272727272727 +Mixtral-8x7B-Instruct-v0.1,evening,3.6435119574237023,326.69,48.545 +Mixtral-8x7B-Instruct-v0.1,late evening,5.62397656769588,395.15714285714284,49.02857142857143 +Mixtral-8x7B-Instruct-v0.1,midnight,4.639010797279158,323.0394736842105,42.69210526315789 +Mixtral-8x7B-Instruct-v0.1,night,4.009439338194697,301.24545454545455,42.21818181818182 +TinyLlama/TinyLlama-1.1B-Chat-v1.0,early morning,2.0273348593711855,372.13,62.53 +TinyLlama/TinyLlama-1.1B-Chat-v1.0,morning,1.9041210174560548,372.05,62.6 +TinyLlama/TinyLlama-1.1B-Chat-v1.0,afternoon,1.8381905496120452,308.795,51.08 +TinyLlama/TinyLlama-1.1B-Chat-v1.0,late afternoon,1.7547113946505954,285.17857142857144,46.9 +TinyLlama/TinyLlama-1.1B-Chat-v1.0,evening,1.7984187936782836,313.99,51.96 +TinyLlama/TinyLlama-1.1B-Chat-v1.0,late evening,1.5875422928068372,192.78333333333333,31.261111111111113 +TinyLlama/TinyLlama-1.1B-Chat-v1.0,midnight,1.6341248273849487,210.2,34.2 +TinyLlama/TinyLlama-1.1B-Chat-v1.0,night,2.0128010153770446,372.05,62.6 +chat-bison,midnight,3.890243631601334,398.075,49.0 +chat-bison (PaLM 2),early morning,2.4665334616388592,381.9214285714286,60.892857142857146 +chat-bison (PaLM 2),morning,2.488477897644043,381.73,60.88 +chat-bison (PaLM 2),afternoon,2.6460144804074215,376.28076923076924,55.965384615384615 +chat-bison (PaLM 2),late afternoon,3.0387172081253744,381.1363636363636,53.35454545454545 +chat-bison (PaLM 2),evening,2.688272579908371,367.07,55.89 +chat-bison (PaLM 2),late evening,2.7250528037548065,382.725,52.95 +chat-bison (PaLM 2),midnight,2.468383938074112,381.95,60.9 +chat-bison (PaLM 2),night,2.460119960308075,381.92,60.94 +chat-bison-32k,midnight,4.128177767992019,389.925,48.025 +chat-bison-32k (PaLM 2 32K),early morning,9.141417106560299,335.75,53.85 +chat-bison-32k (PaLM 2 32K),morning,7.7035503840446475,335.75,53.85 +chat-bison-32k (PaLM 2 32K),afternoon,5.014458654477046,339.3692307692308,49.323076923076925 +chat-bison-32k (PaLM 2 32K),late afternoon,4.5047362284226855,348.65909090909093,48.35454545454545 +chat-bison-32k (PaLM 2 32K),evening,7.7332194912433625,329.46,49.5 +chat-bison-32k (PaLM 2 32K),late evening,7.796841062307358,349.95,47.805 +chat-bison-32k (PaLM 2 32K),midnight,7.7498266498247785,335.75,53.85 +chat-bison-32k (PaLM 2 32K),night,6.491292915344238,335.75,53.85 +gemini-pro,early morning,2.7453590130460435,381.2214285714286,60.964285714285715 +gemini-pro,morning,2.497767536007628,371.93,59.39 +gemini-pro,afternoon,2.816922114008949,360.62307692307695,53.25769230769231 +gemini-pro,late afternoon,2.9268629640903114,364.57272727272726,50.1 +gemini-pro,evening,2.86901999375759,366.4,55.045 +gemini-pro,late evening,3.7189874940246117,390.9142857142857,51.35 +gemini-pro,midnight,3.338477972348531,369.825,55.9125 +gemini-pro,night,2.8375814715210272,374.8,60.04 +gpt-3.5-turbo,early morning,3.787998208734724,403.74444444444447,47.34444444444444 +gpt-3.5-turbo,morning,3.126271222697364,389.9888888888889,50.93888888888889 +gpt-3.5-turbo,afternoon,3.9458200880459375,381.4428571428571,43.76190476190476 +gpt-3.5-turbo,late afternoon,4.384064777692159,396.4357142857143,43.28333333333333 +gpt-3.5-turbo,evening,3.5153889304115657,385.18095238095236,46.01428571428571 +gpt-3.5-turbo,late evening,5.110168156187617,422.73510971786834,45.358934169278996 +gpt-3.5-turbo,midnight,3.822115447632102,426.71923076923076,49.05 +gpt-3.5-turbo,night,6.062970260473398,418.6192307692308,44.926923076923075 +gpt-4,early morning,14.348626694414351,323.5388888888889,40.544444444444444 +gpt-4,morning,12.759107512468733,338.18333333333334,46.85 +gpt-4,afternoon,16.002364798386893,318.3095238095238,38.77142857142857 +gpt-4,late afternoon,16.80607506932254,313.3595238095238,37.49285714285714 +gpt-4,evening,13.841120740345547,318.0809523809524,40.19285714285714 +gpt-4,late evening,14.298642643005493,314.336,37.012 +gpt-4,midnight,12.3578163115329,334.075,41.35 +gpt-4,night,12.813134506115546,316.93461538461537,37.93076923076923 +gpt-4-turbo,early morning,11.555620827939775,357.65555555555557,47.21666666666667 +gpt-4-turbo,morning,13.686854598257277,381.8888888888889,55.02777777777778 +gpt-4-turbo,afternoon,13.997754749229976,351.01190476190476,46.03333333333333 +gpt-4-turbo,late afternoon,22.320911452883767,381.65714285714284,47.35476190476191 +gpt-4-turbo,evening,16.550320884159632,382.31666666666666,48.45 +gpt-4-turbo,late evening,14.592236209392548,413.61,44.8 +gpt-4-turbo,midnight,13.770663784850727,382.7613636363636,47.61818181818182 +gpt-4-turbo,night,14.254795966698573,352.54615384615386,46.37692307692308 +llama-2-70b-chat,early morning,2.8660141522424265,289.6642857142857,44.614285714285714 +llama-2-70b-chat,morning,2.872361832027194,283.35,43.45 +llama-2-70b-chat,afternoon,4.234376892130426,375.44615384615383,55.238461538461536 +llama-2-70b-chat,late afternoon,3.6833307104881365,433.6636363636364,59.445454545454545 +llama-2-70b-chat,evening,2.9706250462084185,317.245,47.4 +llama-2-70b-chat,late evening,4.719581684340602,572.1689655172414,79.83103448275862 +llama-2-70b-chat,midnight,3.249819871626402,346.8875,52.06875 +llama-2-70b-chat,night,2.8264514451677147,313.71,48.42 +zephyr-7b-beta,early morning,3.937663261095683,273.03333333333336,43.45 +zephyr-7b-beta,morning,4.056525647640228,386.3,63.35 +zephyr-7b-beta,afternoon,3.5789777278900146,277.6,44.016666666666666 +zephyr-7b-beta,late afternoon,3.4592524923459447,248.59,38.9 +zephyr-7b-beta,evening,3.5673056403795878,273.3666666666667,43.5 +zephyr-7b-beta,late evening,3.45343524068594,176.23125,27.21875 +zephyr-7b-beta,midnight,3.7253047794103624,217.82083333333333,33.67916666666667 +zephyr-7b-beta,night,3.6954557319482166,216.55833333333334,33.46666666666667 diff --git a/data/general_plots.csv b/data/general_plots.csv new file mode 100644 index 0000000000000000000000000000000000000000..772ecc7dc37f973ad1b08a56a18da97c7ce93dc7 --- /dev/null +++ b/data/general_plots.csv @@ -0,0 +1,452 @@ +path,plot_object,header,description,plot_json +./html/plots/response_times.html,"Figure({ + 'data': [{'alignmentgroup': 'True', + 'hovertemplate': 'Model=%{x}
Execution time (s)=%{y}', + 'legendgroup': 'Mistral-7B-Instruct-v0.2', + 'marker': {'color': '#636efa', 'pattern': {'shape': ''}}, + 'name': 'Mistral-7B-Instruct-v0.2', + 'offsetgroup': 'Mistral-7B-Instruct-v0.2', + 'orientation': 'v', + 'showlegend': True, + 'textposition': 'auto', + 'type': 'bar', + 'x': array(['Mistral-7B-Instruct-v0.2'], dtype=object), + 'xaxis': 'x', + 'y': array([3.27102681]), + 'yaxis': 'y'}, + {'alignmentgroup': 'True', + 'hovertemplate': 'Model=%{x}
Execution time (s)=%{y}', + 'legendgroup': 'Mixtral-8x7B-Instruct-v0.1', + 'marker': {'color': '#EF553B', 'pattern': {'shape': ''}}, + 'name': 'Mixtral-8x7B-Instruct-v0.1', + 'offsetgroup': 'Mixtral-8x7B-Instruct-v0.1', + 'orientation': 'v', + 'showlegend': True, + 'textposition': 'auto', + 'type': 'bar', + 'x': array(['Mixtral-8x7B-Instruct-v0.1'], dtype=object), + 'xaxis': 'x', + 'y': array([4.83500647]), + 'yaxis': 'y'}, + {'alignmentgroup': 'True', + 'hovertemplate': 'Model=%{x}
Execution time (s)=%{y}', + 'legendgroup': 'TinyLlama/TinyLlama-1.1B-Chat-v1.0', + 'marker': {'color': '#00cc96', 'pattern': {'shape': ''}}, + 'name': 'TinyLlama/TinyLlama-1.1B-Chat-v1.0', + 'offsetgroup': 'TinyLlama/TinyLlama-1.1B-Chat-v1.0', + 'orientation': 'v', + 'showlegend': True, + 'textposition': 'auto', + 'type': 'bar', + 'x': array(['TinyLlama/TinyLlama-1.1B-Chat-v1.0'], dtype=object), + 'xaxis': 'x', + 'y': array([1.79273835]), + 'yaxis': 'y'}, + {'alignmentgroup': 'True', + 'hovertemplate': 'Model=%{x}
Execution time (s)=%{y}', + 'legendgroup': 'chat-bison', + 'marker': {'color': '#ab63fa', 'pattern': {'shape': ''}}, + 'name': 'chat-bison', + 'offsetgroup': 'chat-bison', + 'orientation': 'v', + 'showlegend': True, + 'textposition': 'auto', + 'type': 'bar', + 'x': array(['chat-bison'], dtype=object), + 'xaxis': 'x', + 'y': array([3.89024363]), + 'yaxis': 'y'}, + {'alignmentgroup': 'True', + 'hovertemplate': 'Model=%{x}
Execution time (s)=%{y}', + 'legendgroup': 'chat-bison (PaLM 2)', + 'marker': {'color': '#FFA15A', 'pattern': {'shape': ''}}, + 'name': 'chat-bison (PaLM 2)', + 'offsetgroup': 'chat-bison (PaLM 2)', + 'orientation': 'v', + 'showlegend': True, + 'textposition': 'auto', + 'type': 'bar', + 'x': array(['chat-bison (PaLM 2)'], dtype=object), + 'xaxis': 'x', + 'y': array([2.66830386]), + 'yaxis': 'y'}, + {'alignmentgroup': 'True', + 'hovertemplate': 'Model=%{x}
Execution time (s)=%{y}', + 'legendgroup': 'chat-bison-32k', + 'marker': {'color': '#19d3f3', 'pattern': {'shape': ''}}, + 'name': 'chat-bison-32k', + 'offsetgroup': 'chat-bison-32k', + 'orientation': 'v', + 'showlegend': True, + 'textposition': 'auto', + 'type': 'bar', + 'x': array(['chat-bison-32k'], dtype=object), + 'xaxis': 'x', + 'y': array([4.12817777]), + 'yaxis': 'y'}, + {'alignmentgroup': 'True', + 'hovertemplate': 'Model=%{x}
Execution time (s)=%{y}', + 'legendgroup': 'chat-bison-32k (PaLM 2 32K)', + 'marker': {'color': '#FF6692', 'pattern': {'shape': ''}}, + 'name': 'chat-bison-32k (PaLM 2 32K)', + 'offsetgroup': 'chat-bison-32k (PaLM 2 32K)', + 'orientation': 'v', + 'showlegend': True, + 'textposition': 'auto', + 'type': 'bar', + 'x': array(['chat-bison-32k (PaLM 2 32K)'], dtype=object), + 'xaxis': 'x', + 'y': array([6.73886213]), + 'yaxis': 'y'}, + {'alignmentgroup': 'True', + 'hovertemplate': 'Model=%{x}
Execution time (s)=%{y}', + 'legendgroup': 'gemini-pro', + 'marker': {'color': '#B6E880', 'pattern': {'shape': ''}}, + 'name': 'gemini-pro', + 'offsetgroup': 'gemini-pro', + 'orientation': 'v', + 'showlegend': True, + 'textposition': 'auto', + 'type': 'bar', + 'x': array(['gemini-pro'], dtype=object), + 'xaxis': 'x', + 'y': array([3.03678889]), + 'yaxis': 'y'}, + {'alignmentgroup': 'True', + 'hovertemplate': 'Model=%{x}
Execution time (s)=%{y}', + 'legendgroup': 'gpt-3.5-turbo', + 'marker': {'color': '#FF97FF', 'pattern': {'shape': ''}}, + 'name': 'gpt-3.5-turbo', + 'offsetgroup': 'gpt-3.5-turbo', + 'orientation': 'v', + 'showlegend': True, + 'textposition': 'auto', + 'type': 'bar', + 'x': array(['gpt-3.5-turbo'], dtype=object), + 'xaxis': 'x', + 'y': array([4.29307391]), + 'yaxis': 'y'}, + {'alignmentgroup': 'True', + 'hovertemplate': 'Model=%{x}
Execution time (s)=%{y}', + 'legendgroup': 'gpt-4', + 'marker': {'color': '#FECB52', 'pattern': {'shape': ''}}, + 'name': 'gpt-4', + 'offsetgroup': 'gpt-4', + 'orientation': 'v', + 'showlegend': True, + 'textposition': 'auto', + 'type': 'bar', + 'x': array(['gpt-4'], dtype=object), + 'xaxis': 'x', + 'y': array([14.32373439]), + 'yaxis': 'y'}, + {'alignmentgroup': 'True', + 'hovertemplate': 'Model=%{x}
Execution time (s)=%{y}', + 'legendgroup': 'gpt-4-turbo', + 'marker': {'color': '#636efa', 'pattern': {'shape': ''}}, + 'name': 'gpt-4-turbo', + 'offsetgroup': 'gpt-4-turbo', + 'orientation': 'v', + 'showlegend': True, + 'textposition': 'auto', + 'type': 'bar', + 'x': array(['gpt-4-turbo'], dtype=object), + 'xaxis': 'x', + 'y': array([15.5354884]), + 'yaxis': 'y'}, + {'alignmentgroup': 'True', + 'hovertemplate': 'Model=%{x}
Execution time (s)=%{y}', + 'legendgroup': 'llama-2-70b-chat', + 'marker': {'color': '#EF553B', 'pattern': {'shape': ''}}, + 'name': 'llama-2-70b-chat', + 'offsetgroup': 'llama-2-70b-chat', + 'orientation': 'v', + 'showlegend': True, + 'textposition': 'auto', + 'type': 'bar', + 'x': array(['llama-2-70b-chat'], dtype=object), + 'xaxis': 'x', + 'y': array([3.6742315]), + 'yaxis': 'y'}, + {'alignmentgroup': 'True', + 'hovertemplate': 'Model=%{x}
Execution time (s)=%{y}', + 'legendgroup': 'zephyr-7b-beta', + 'marker': {'color': '#00cc96', 'pattern': {'shape': ''}}, + 'name': 'zephyr-7b-beta', + 'offsetgroup': 'zephyr-7b-beta', + 'orientation': 'v', + 'showlegend': True, + 'textposition': 'auto', + 'type': 'bar', + 'x': array(['zephyr-7b-beta'], dtype=object), + 'xaxis': 'x', + 'y': array([3.6370095]), + 'yaxis': 'y'}], + 'layout': {'barmode': 'relative', + 'legend': {'title': {'text': 'Model'}, 'tracegroupgap': 0}, + 'template': '...', + 'title': {'text': 'Model endpoints response times'}, + 'xaxis': {'anchor': 'y', + 'categoryarray': [Mistral-7B-Instruct-v0.2, + Mixtral-8x7B-Instruct-v0.1, + TinyLlama/TinyLlama-1.1B-Chat-v1.0, + chat-bison, chat-bison (PaLM 2), chat- + bison-32k, chat-bison-32k (PaLM 2 32K), + gemini-pro, gpt-3.5-turbo, gpt-4, + gpt-4-turbo, llama-2-70b-chat, + zephyr-7b-beta], + 'categoryorder': 'array', + 'domain': [0.0, 1.0], + 'title': {'text': 'Model'}}, + 'yaxis': {'anchor': 'x', 'domain': [0.0, 1.0], 'title': {'text': 'Execution time (s)'}}} +})",Model endpoints response times,"This plot shows averaged response time for one query for each model. + +We used `time.time()` result saved to variable before making the call to API and compared it to `time.time()` result after receiving the results. + +It is also important to note that we used litellm python library for all of the models which adds some overhead compared to pure curl calls.","{""data"":[{""alignmentgroup"":""True"",""hovertemplate"":""Model=%{x}\u003cbr\u003eExecution time 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Execution time (s)=%{y}', + 'legendgroup': 'Mixtral-8x7B-Instruct-v0.1', + 'marker': {'color': '#EF553B', 'pattern': {'shape': ''}}, + 'name': 'Mixtral-8x7B-Instruct-v0.1', + 'offsetgroup': 'Mixtral-8x7B-Instruct-v0.1', + 'orientation': 'v', + 'showlegend': True, + 'textposition': 'auto', + 'type': 'bar', + 'x': array(['Mixtral-8x7B-Instruct-v0.1'], dtype=object), + 'xaxis': 'x', + 'y': array([6.88927143]), + 'yaxis': 'y'}, + {'alignmentgroup': 'True', + 'hovertemplate': 'Model=%{x}
Execution time (s)=%{y}', + 'legendgroup': 'TinyLlama/TinyLlama-1.1B-Chat-v1.0', + 'marker': {'color': '#00cc96', 'pattern': {'shape': ''}}, + 'name': 'TinyLlama/TinyLlama-1.1B-Chat-v1.0', + 'offsetgroup': 'TinyLlama/TinyLlama-1.1B-Chat-v1.0', + 'orientation': 'v', + 'showlegend': True, + 'textposition': 'auto', + 'type': 'bar', + 'x': array(['TinyLlama/TinyLlama-1.1B-Chat-v1.0'], dtype=object), + 'xaxis': 'x', + 'y': array([1.59549656]), + 'yaxis': 'y'}, + {'alignmentgroup': 'True', + 'hovertemplate': 'Model=%{x}
Execution time (s)=%{y}', + 'legendgroup': 'chat-bison', + 'marker': {'color': '#ab63fa', 'pattern': {'shape': ''}}, + 'name': 'chat-bison', + 'offsetgroup': 'chat-bison', + 'orientation': 'v', + 'showlegend': True, + 'textposition': 'auto', + 'type': 'bar', + 'x': array(['chat-bison'], dtype=object), + 'xaxis': 'x', + 'y': array([3.89024363]), + 'yaxis': 'y'}, + {'alignmentgroup': 'True', + 'hovertemplate': 'Model=%{x}
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