Corey Morris
commited on
Commit
•
e79bcf3
1
Parent(s):
d506f10
Fixed type error
Browse files- app.py +1 -1
- result_data_processor.py +6 -5
app.py
CHANGED
@@ -105,7 +105,7 @@ def create_line_chart(df, model_names, metrics):
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fig.update_layout(showlegend=True)
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return fig
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-
def find_top_differences_table(df, target_model, closest_models, num_differences=10, exclude_columns=['Parameters']):
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# Calculate the absolute differences for each task between the target model and the closest models
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new_df = df.drop(columns=exclude_columns)
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differences = new_df.loc[closest_models].sub(new_df.loc[target_model]).abs()
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fig.update_layout(showlegend=True)
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return fig
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+
def find_top_differences_table(df, target_model, closest_models, num_differences=10, exclude_columns=['Parameters', 'organization']):
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# Calculate the absolute differences for each task between the target model and the closest models
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new_df = df.drop(columns=exclude_columns)
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differences = new_df.loc[closest_models].sub(new_df.loc[target_model]).abs()
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result_data_processor.py
CHANGED
@@ -89,6 +89,7 @@ class ResultDataProcessor:
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def process_data(self):
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dataframes = []
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for filename in self._find_files(self.directory, self.pattern):
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raw_data = self._read_and_transform_data(filename)
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split_path = filename.split('/')
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@@ -99,13 +100,15 @@ class ResultDataProcessor:
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mc2 = self._extract_mc2(raw_data, model_name)
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cleaned_data = pd.concat([cleaned_data, mc1])
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cleaned_data = pd.concat([cleaned_data, mc2])
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-
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-
cleaned_data.loc['organization'] = organization_name
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dataframes.append(cleaned_data)
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data = pd.concat(dataframes, axis=1).transpose()
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-
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# Add Model Name and rearrange columns
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data['Model Name'] = data.index
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cols = data.columns.tolist()
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@@ -137,8 +140,6 @@ class ResultDataProcessor:
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# remove extreme outliers from column harness|truthfulqa:mc1
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data = self._remove_mc1_outliers(data)
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-
data = data.drop(columns=['organization'])
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-
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return data
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def rank_data(self):
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def process_data(self):
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dataframes = []
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+
organization_names = []
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for filename in self._find_files(self.directory, self.pattern):
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raw_data = self._read_and_transform_data(filename)
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split_path = filename.split('/')
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mc2 = self._extract_mc2(raw_data, model_name)
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cleaned_data = pd.concat([cleaned_data, mc1])
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cleaned_data = pd.concat([cleaned_data, mc2])
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+
organization_names.append(organization_name)
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dataframes.append(cleaned_data)
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data = pd.concat(dataframes, axis=1).transpose()
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# Add organization column
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data['organization'] = organization_names
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+
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# Add Model Name and rearrange columns
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data['Model Name'] = data.index
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cols = data.columns.tolist()
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# remove extreme outliers from column harness|truthfulqa:mc1
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data = self._remove_mc1_outliers(data)
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return data
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def rank_data(self):
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