--- base_model: bobox/DeBERTa-small-ST-v1-test-step2 datasets: - tals/vitaminc - allenai/scitail - allenai/sciq - allenai/qasc - sentence-transformers/msmarco-msmarco-distilbert-base-v3 - sentence-transformers/natural-questions - sentence-transformers/trivia-qa - sentence-transformers/gooaq - google-research-datasets/paws language: - en library_name: sentence-transformers metrics: - pearson_cosine - spearman_cosine - pearson_manhattan - spearman_manhattan - pearson_euclidean - spearman_euclidean - pearson_dot - spearman_dot - pearson_max - spearman_max - cosine_accuracy - cosine_accuracy_threshold - cosine_f1 - cosine_f1_threshold - cosine_precision - cosine_recall - cosine_ap - dot_accuracy - dot_accuracy_threshold - dot_f1 - dot_f1_threshold - dot_precision - dot_recall - dot_ap - manhattan_accuracy - manhattan_accuracy_threshold - manhattan_f1 - manhattan_f1_threshold - manhattan_precision - manhattan_recall - manhattan_ap - euclidean_accuracy - euclidean_accuracy_threshold - euclidean_f1 - euclidean_f1_threshold - euclidean_precision - euclidean_recall - euclidean_ap - max_accuracy - max_accuracy_threshold - max_f1 - max_f1_threshold - max_precision - max_recall - max_ap pipeline_tag: sentence-similarity tags: - sentence-transformers - sentence-similarity - feature-extraction - generated_from_trainer - dataset_size:279409 - loss:CachedGISTEmbedLoss widget: - source_sentence: what is acetylcholinesterase in biochemistry sentences: - The Arkansas was the last nuclear powered cruiser built by the United States. (Click here for detailed information about the USS Arkansas) USS Enterprise (CVN-65) The USS Enterprise was the Navy's first nuclear powered aircraft carrier and from 1961 to 1972 she was the biggest warship in the world. - The staph infection may also live on the skin of a dog as a parasite or in the respiratory system of a dog. In some cases if a dog is not treated right away the dog could become very ill or even die. In some cases where a dog is infected with staph a dog may have one or several different symptoms. These signs may be a reason to have a dog seen by a veterinarian; typically this disease may make a dog very sick. Some symptoms of staph infection may include but are not limited to. - Acetylcholinesterase (HGNC symbol ACHE), also known as AChE or acetylhydrolase, is the primary cholinesterase in the body.It is an enzyme that catalyzes the breakdown of acetylcholine and of some other choline esters that function as neurotransmitters.AChE is found at mainly neuromuscular junctions and in chemical synapses of the cholinergic type, where its activity serves to terminate synaptic transmission.uring neurotransmission, ACh is released from the nerve into the synaptic cleft and binds to ACh receptors on the post-synaptic membrane, relaying the signal from the nerve. AChE, also located on the post-synaptic membrane, terminates the signal transmission by hydrolyzing ACh. - source_sentence: More than 169 countries had reported over 212,000 COVID-19 cases before March 19 , 2020 . sentences: - As of 23 March , more than 341,000 cases of COVID-19 have been reported in 192 countries and territories , resulting in more than 14,700 deaths and 99,000 recoveries . - As of 21 March , more than 278,000 cases of COVID-19 have been reported in over 186 countries and territories , resulting in more than 11,500 deaths and 92,000 recoveries. virus seems to mostly spread between people via respiratory droplets . - As of 18 March 2020 , more than 212,000 cases of COVID-19 have been reported in at least 170 countries and territories , with major outbreaks in China , Iran and the European Union . - source_sentence: The brain is harmed if you get meningitis. sentences: - Which organ of our body is harmed if you get meningitis? - What is the rate at which a specific allele appears within a population called? - What is the term for the application of science to solve problems? - source_sentence: Electrical energy can be converted into kinetic energy and heat energy by an electric motor. sentences: - Solution is the term for a homogeneous mixture of two or more substances. - Solution is the term for a homogeneous mixture of two or more substances. - Electric motors transform electrical energy into kinetic energy. - source_sentence: where was the first hudson bay company post sentences: - Hudson's Bay Company Hudson's Bay Company's first inland trading post was established by Samuel Hearne in 1774 in Cumberland House, Saskatchewan.[38][39] - Another Mother for Peace Los Angeles artist Lorraine Art Schneider donated the use of a striking illustration for the Mother's Day peace cards--a sunflower on yellow background amid the slogan “War is not healthy for children and other living things.” [1] - Steven Ogg Steven Ogg is a Canadian actor.[1] He is best known for his roles as Trevor Philips in the 2013 video game Grand Theft Auto V and Simon in The Walking Dead.[2] He has also appeared in television series such as Better Call Saul, Law & Order, Person of Interest, Broad City, and Westworld. model-index: - name: SentenceTransformer based on bobox/DeBERTa-small-ST-v1-test-step2 results: - task: type: semantic-similarity name: Semantic Similarity dataset: name: sts test type: sts-test metrics: - type: pearson_cosine value: 0.8861432363248951 name: Pearson Cosine - type: spearman_cosine value: 0.9077370026312627 name: Spearman Cosine - type: pearson_manhattan value: 0.9086667636630104 name: Pearson Manhattan - type: spearman_manhattan value: 0.9042784013946286 name: Spearman Manhattan - type: pearson_euclidean value: 0.9079766073019917 name: Pearson Euclidean - type: spearman_euclidean value: 0.903971004980131 name: Spearman Euclidean - type: pearson_dot value: 0.8769458596903497 name: Pearson Dot - type: spearman_dot value: 0.879439974530776 name: Spearman Dot - type: pearson_max value: 0.9086667636630104 name: Pearson Max - type: spearman_max value: 0.9077370026312627 name: Spearman Max - task: type: binary-classification name: Binary Classification dataset: name: VitaminC type: VitaminC metrics: - type: cosine_accuracy value: 0.5546875 name: Cosine Accuracy - type: cosine_accuracy_threshold value: 0.8242440819740295 name: Cosine Accuracy Threshold - type: cosine_f1 value: 0.6684856753069577 name: Cosine F1 - type: cosine_f1_threshold value: 0.42694979906082153 name: Cosine F1 Threshold - type: cosine_precision value: 0.508298755186722 name: Cosine Precision - type: cosine_recall value: 0.9760956175298805 name: Cosine Recall - type: cosine_ap value: 0.5536891122484903 name: Cosine Ap - type: dot_accuracy value: 0.548828125 name: Dot Accuracy - type: dot_accuracy_threshold value: 320.12664794921875 name: Dot Accuracy Threshold - type: dot_f1 value: 0.6711772665764546 name: Dot F1 - type: dot_f1_threshold value: 147.43307495117188 name: Dot F1 Threshold - type: dot_precision value: 0.5081967213114754 name: Dot Precision - type: dot_recall value: 0.9880478087649402 name: Dot Recall - type: dot_ap value: 0.5328419714769899 name: Dot Ap - type: manhattan_accuracy value: 0.556640625 name: Manhattan Accuracy - type: manhattan_accuracy_threshold value: 317.9842224121094 name: Manhattan Accuracy Threshold - type: manhattan_f1 value: 0.6649006622516557 name: Manhattan F1 - type: manhattan_f1_threshold value: 510.47943115234375 name: Manhattan F1 Threshold - type: manhattan_precision value: 0.498015873015873 name: Manhattan Precision - type: manhattan_recall value: 1.0 name: Manhattan Recall - type: manhattan_ap value: 0.5558452170498778 name: Manhattan Ap - type: euclidean_accuracy value: 0.5625 name: Euclidean Accuracy - type: euclidean_accuracy_threshold value: 15.206985473632812 name: Euclidean Accuracy Threshold - type: euclidean_f1 value: 0.6657789613848203 name: Euclidean F1 - type: euclidean_f1_threshold value: 22.77822494506836 name: Euclidean F1 Threshold - type: euclidean_precision value: 0.5 name: Euclidean Precision - type: euclidean_recall value: 0.9960159362549801 name: Euclidean Recall - type: euclidean_ap value: 0.5563017058033936 name: Euclidean Ap - type: max_accuracy value: 0.5625 name: Max Accuracy - type: max_accuracy_threshold value: 320.12664794921875 name: Max Accuracy Threshold - type: max_f1 value: 0.6711772665764546 name: Max F1 - type: max_f1_threshold value: 510.47943115234375 name: Max F1 Threshold - type: max_precision value: 0.508298755186722 name: Max Precision - type: max_recall value: 1.0 name: Max Recall - type: max_ap value: 0.5563017058033936 name: Max Ap --- # SentenceTransformer based on bobox/DeBERTa-small-ST-v1-test-step2 This is a [sentence-transformers](https://www.SBERT.net) model finetuned from [bobox/DeBERTa-small-ST-v1-test-step2](https://huggingface.co/bobox/DeBERTa-small-ST-v1-test-step2) on the negation-triplets, [vitaminc-pairs](https://huggingface.co/datasets/tals/vitaminc), [scitail-pairs-qa](https://huggingface.co/datasets/allenai/scitail), [scitail-pairs-pos](https://huggingface.co/datasets/allenai/scitail), xsum-pairs, [sciq_pairs](https://huggingface.co/datasets/allenai/sciq), [qasc_pairs](https://huggingface.co/datasets/allenai/qasc), openbookqa_pairs, [msmarco_pairs](https://huggingface.co/datasets/sentence-transformers/msmarco-msmarco-distilbert-base-v3), [nq_pairs](https://huggingface.co/datasets/sentence-transformers/natural-questions), [trivia_pairs](https://huggingface.co/datasets/sentence-transformers/trivia-qa), [gooaq_pairs](https://huggingface.co/datasets/sentence-transformers/gooaq) and [paws-pos](https://huggingface.co/datasets/google-research-datasets/paws) datasets. It maps sentences & paragraphs to a 768-dimensional dense vector space and can be used for semantic textual similarity, semantic search, paraphrase mining, text classification, clustering, and more. ## Model Details ### Model Description - **Model Type:** Sentence Transformer - **Base model:** [bobox/DeBERTa-small-ST-v1-test-step2](https://huggingface.co/bobox/DeBERTa-small-ST-v1-test-step2) - **Maximum Sequence Length:** 512 tokens - **Output Dimensionality:** 768 tokens - **Similarity Function:** Cosine Similarity - **Training Datasets:** - negation-triplets - [vitaminc-pairs](https://huggingface.co/datasets/tals/vitaminc) - [scitail-pairs-qa](https://huggingface.co/datasets/allenai/scitail) - [scitail-pairs-pos](https://huggingface.co/datasets/allenai/scitail) - xsum-pairs - [sciq_pairs](https://huggingface.co/datasets/allenai/sciq) - [qasc_pairs](https://huggingface.co/datasets/allenai/qasc) - openbookqa_pairs - [msmarco_pairs](https://huggingface.co/datasets/sentence-transformers/msmarco-msmarco-distilbert-base-v3) - [nq_pairs](https://huggingface.co/datasets/sentence-transformers/natural-questions) - [trivia_pairs](https://huggingface.co/datasets/sentence-transformers/trivia-qa) - [gooaq_pairs](https://huggingface.co/datasets/sentence-transformers/gooaq) - [paws-pos](https://huggingface.co/datasets/google-research-datasets/paws) - **Language:** en ### Model Sources - **Documentation:** [Sentence Transformers Documentation](https://sbert.net) - **Repository:** [Sentence Transformers on GitHub](https://github.com/UKPLab/sentence-transformers) - **Hugging Face:** [Sentence Transformers on Hugging Face](https://huggingface.co/models?library=sentence-transformers) ### Full Model Architecture ``` SentenceTransformer( (0): Transformer({'max_seq_length': 512, 'do_lower_case': False}) with Transformer model: DebertaV2Model (1): Pooling({'word_embedding_dimension': 768, 'pooling_mode_cls_token': False, 'pooling_mode_mean_tokens': True, 'pooling_mode_max_tokens': False, 'pooling_mode_mean_sqrt_len_tokens': False, 'pooling_mode_weightedmean_tokens': False, 'pooling_mode_lasttoken': False, 'include_prompt': True}) ) ``` ## Usage ### Direct Usage (Sentence Transformers) First install the Sentence Transformers library: ```bash pip install -U sentence-transformers ``` Then you can load this model and run inference. ```python from sentence_transformers import SentenceTransformer # Download from the 🤗 Hub model = SentenceTransformer("bobox/DeBERTa-small-ST-v1-test-step3") # Run inference sentences = [ 'where was the first hudson bay company post', "Hudson's Bay Company Hudson's Bay Company's first inland trading post was established by Samuel Hearne in 1774 in Cumberland House, Saskatchewan.[38][39]", 'Steven Ogg Steven Ogg is a Canadian actor.[1] He is best known for his roles as Trevor Philips in the 2013 video game Grand Theft Auto V and Simon in The Walking Dead.[2] He has also appeared in television series such as Better Call Saul, Law & Order, Person of Interest, Broad City, and Westworld.', ] embeddings = model.encode(sentences) print(embeddings.shape) # [3, 768] # Get the similarity scores for the embeddings similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [3, 3] ``` ## Evaluation ### Metrics #### Semantic Similarity * Dataset: `sts-test` * Evaluated with [EmbeddingSimilarityEvaluator](https://sbert.net/docs/package_reference/sentence_transformer/evaluation.html#sentence_transformers.evaluation.EmbeddingSimilarityEvaluator) | Metric | Value | |:--------------------|:-----------| | pearson_cosine | 0.8861 | | **spearman_cosine** | **0.9077** | | pearson_manhattan | 0.9087 | | spearman_manhattan | 0.9043 | | pearson_euclidean | 0.908 | | spearman_euclidean | 0.904 | | pearson_dot | 0.8769 | | spearman_dot | 0.8794 | | pearson_max | 0.9087 | | spearman_max | 0.9077 | #### Binary Classification * Dataset: `VitaminC` * Evaluated with [BinaryClassificationEvaluator](https://sbert.net/docs/package_reference/sentence_transformer/evaluation.html#sentence_transformers.evaluation.BinaryClassificationEvaluator) | Metric | Value | |:-----------------------------|:-----------| | cosine_accuracy | 0.5547 | | cosine_accuracy_threshold | 0.8242 | | cosine_f1 | 0.6685 | | cosine_f1_threshold | 0.4269 | | cosine_precision | 0.5083 | | cosine_recall | 0.9761 | | cosine_ap | 0.5537 | | dot_accuracy | 0.5488 | | dot_accuracy_threshold | 320.1266 | | dot_f1 | 0.6712 | | dot_f1_threshold | 147.4331 | | dot_precision | 0.5082 | | dot_recall | 0.988 | | dot_ap | 0.5328 | | manhattan_accuracy | 0.5566 | | manhattan_accuracy_threshold | 317.9842 | | manhattan_f1 | 0.6649 | | manhattan_f1_threshold | 510.4794 | | manhattan_precision | 0.498 | | manhattan_recall | 1.0 | | manhattan_ap | 0.5558 | | euclidean_accuracy | 0.5625 | | euclidean_accuracy_threshold | 15.207 | | euclidean_f1 | 0.6658 | | euclidean_f1_threshold | 22.7782 | | euclidean_precision | 0.5 | | euclidean_recall | 0.996 | | euclidean_ap | 0.5563 | | max_accuracy | 0.5625 | | max_accuracy_threshold | 320.1266 | | max_f1 | 0.6712 | | max_f1_threshold | 510.4794 | | max_precision | 0.5083 | | max_recall | 1.0 | | **max_ap** | **0.5563** | ## Training Details ### Training Datasets #### negation-triplets * Dataset: negation-triplets * Size: 35,750 training samples * Columns: anchor, entailment, and negative * Approximate statistics based on the first 1000 samples: | | anchor | entailment | negative | |:--------|:-----------------------------------------------------------------------------------|:----------------------------------------------------------------------------------|:----------------------------------------------------------------------------------| | type | string | string | string | | details | | | | * Samples: | anchor | entailment | negative | |:--------------------------------------------------------------------------------|:--------------------------------------------------------------------------------|:------------------------------------------------------------------------------------| | Brunette woman in a white bikini pouring a drink into a man's cup. | A woman is serving a beverage to a man. | A woman is not serving a beverage to a man. | | People under a tent at a reception. | People are outside. | People are inside. | | A man is smoking at sunset. | The time in the picture is probably somewhere between 3PM and 9PM. | The time in the picture is probably not somewhere between 3PM and 9PM. | * Loss: [CachedGISTEmbedLoss](https://sbert.net/docs/package_reference/sentence_transformer/losses.html#cachedgistembedloss) with these parameters: ```json {'guide': SentenceTransformer( (0): Transformer({'max_seq_length': 512, 'do_lower_case': False}) with Transformer model: BertModel (1): Pooling({'word_embedding_dimension': 768, 'pooling_mode_cls_token': True, 'pooling_mode_mean_tokens': False, 'pooling_mode_max_tokens': False, 'pooling_mode_mean_sqrt_len_tokens': False, 'pooling_mode_weightedmean_tokens': False, 'pooling_mode_lasttoken': False, 'include_prompt': True}) (2): Normalize() ), 'temperature': 0.05} ``` #### vitaminc-pairs * Dataset: [vitaminc-pairs](https://huggingface.co/datasets/tals/vitaminc) at [be6febb](https://huggingface.co/datasets/tals/vitaminc/tree/be6febb761b0b2807687e61e0b5282e459df2fa0) * Size: 34,375 training samples * Columns: claim and evidence * Approximate statistics based on the first 1000 samples: | | claim | evidence | |:--------|:----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------| | type | string | string | | details | | | * Samples: | claim | evidence | |:----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------| | Dora and the Lost City of Gold grossed more than $ 58 million in North America , more than $ 40 million in other territories , and more than $ 98 million globally . | , Dora and the Lost City of Gold has grossed $ 58.4 million in the United States and Canada , and $ 40.4 million in other territories , for a worldwide total of $ 98.8 million , against a production budget of $ 49 million . | | After Juan Antonio and Vicky Cristina have sex , they go to bed . | Afterwards , Juan Antonio lets her know he thinks she 's beautiful , and they make love , and eventually go to bed . | | Tove Lo 's single `` Disco Tits '' reached number 55 in Sweden . | `` Its lead single , `` '' Disco Tits '' '' , peaked at number 55 in Sweden. '' | * Loss: [CachedGISTEmbedLoss](https://sbert.net/docs/package_reference/sentence_transformer/losses.html#cachedgistembedloss) with these parameters: ```json {'guide': SentenceTransformer( (0): Transformer({'max_seq_length': 512, 'do_lower_case': False}) with Transformer model: BertModel (1): Pooling({'word_embedding_dimension': 768, 'pooling_mode_cls_token': True, 'pooling_mode_mean_tokens': False, 'pooling_mode_max_tokens': False, 'pooling_mode_mean_sqrt_len_tokens': False, 'pooling_mode_weightedmean_tokens': False, 'pooling_mode_lasttoken': False, 'include_prompt': True}) (2): Normalize() ), 'temperature': 0.05} ``` #### scitail-pairs-qa * Dataset: [scitail-pairs-qa](https://huggingface.co/datasets/allenai/scitail) at [0cc4353](https://huggingface.co/datasets/allenai/scitail/tree/0cc4353235b289165dfde1c7c5d1be983f99ce44) * Size: 14,237 training samples * Columns: sentence2 and question * Approximate statistics based on the first 1000 samples: | | sentence2 | question | |:--------|:----------------------------------------------------------------------------------|:----------------------------------------------------------------------------------| | type | string | string | | details | | | * Samples: | sentence2 | question | |:--------------------------------------------------------------------------|:--------------------------------------------------------------------| | When an atom gains or loses an electron it becames a(n) ion. | When an atom gains or loses an electron it becames an? | | The stratosphere is the layer above the troposphere. | What is the layer above the troposphere? | | Solar and wind are still expensive compared to fossil fuels. | Solar and wind are still expensive compared to what? | * Loss: [CachedGISTEmbedLoss](https://sbert.net/docs/package_reference/sentence_transformer/losses.html#cachedgistembedloss) with these parameters: ```json {'guide': SentenceTransformer( (0): Transformer({'max_seq_length': 512, 'do_lower_case': False}) with Transformer model: BertModel (1): Pooling({'word_embedding_dimension': 768, 'pooling_mode_cls_token': True, 'pooling_mode_mean_tokens': False, 'pooling_mode_max_tokens': False, 'pooling_mode_mean_sqrt_len_tokens': False, 'pooling_mode_weightedmean_tokens': False, 'pooling_mode_lasttoken': False, 'include_prompt': True}) (2): Normalize() ), 'temperature': 0.05} ``` #### scitail-pairs-pos * Dataset: [scitail-pairs-pos](https://huggingface.co/datasets/allenai/scitail) at [0cc4353](https://huggingface.co/datasets/allenai/scitail/tree/0cc4353235b289165dfde1c7c5d1be983f99ce44) * Size: 8,600 training samples * Columns: sentence1 and sentence2 * Approximate statistics based on the first 1000 samples: | | sentence1 | sentence2 | |:--------|:----------------------------------------------------------------------------------|:----------------------------------------------------------------------------------| | type | string | string | | details | | | * Samples: | sentence1 | sentence2 | |:--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:---------------------------------------------------------------------------------------| | Ozone is a molecule formed of THREE oxygen atoms. | Three oxygen ions make up an ozone molecule. | | Animals live by eating the energy produced by plants (herbivores), or live by eating animals that eat plants (carnivores) Let's take the human being (a polyhagous animal) as an example and ponder upon it. | Herbivores is the term for animals that eat producers to get energy. | | Fertilization triggers Meiosis II, and then the sperm nucleus unites with the resulting egg nucleus. | When a sperm penetrates the egg, it triggers the egg to complete meiosis. | * Loss: [CachedGISTEmbedLoss](https://sbert.net/docs/package_reference/sentence_transformer/losses.html#cachedgistembedloss) with these parameters: ```json {'guide': SentenceTransformer( (0): Transformer({'max_seq_length': 512, 'do_lower_case': False}) with Transformer model: BertModel (1): Pooling({'word_embedding_dimension': 768, 'pooling_mode_cls_token': True, 'pooling_mode_mean_tokens': False, 'pooling_mode_max_tokens': False, 'pooling_mode_mean_sqrt_len_tokens': False, 'pooling_mode_weightedmean_tokens': False, 'pooling_mode_lasttoken': False, 'include_prompt': True}) (2): Normalize() ), 'temperature': 0.05} ``` #### xsum-pairs * Dataset: xsum-pairs * Size: 38,500 training samples * Columns: document and summary * Approximate statistics based on the first 1000 samples: | | document | summary | |:--------|:-------------------------------------------------------------------------------------|:----------------------------------------------------------------------------------| | type | string | string | | details | | | * Samples: | document | summary | |:-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------------------------------------------------------------------------------| | William Heath, 12, from Earls Barton, has so far disguised himself as Ali G, Hercule Poirot and Groucho Marx as part of his Movember campaign.
He is raising money in memory of his grandfather, who died from cancer in February.
William came up with the idea as he cannot grow a moustache himself.
His granddad, Robin Wickham, died from pancreatic, testicular and prostate cancer, and William is now asking people to donate to The Movember Foundation, via his own "Mo Space" page.
William has already dressed as seven famous moustachioed men, including Biggles, Keith Lemon and Magnum PI.
His costumes were sourced from a combination of a local fancy dress shop and items around the home.
"My granddad and I were very close," he said. "He used to come on holiday with us and was always having fun."
His mum Clare said William had wanted to do something that would help, but was also fun.
She said: "We needed to fill 30 days. When you try to think of 30 people with moustaches it is harder than you think.
"The overriding thing is that it has been fun, but it has serious implications."
William said his favourite character so far had been Ali G, but he had struggled to create a successful Ned Flanders outfit.
He said: "I tried to paint my face yellow, but it didn't really work." | A schoolboy has decided to raise money for a men's health charity by dressing up as a different moustachioed famous face every day for a month. | | Media playback is not supported on this device
The Daily Mail claimed a £10m offer was made to owner Owen Oyston despite him stating the club was not for sale at a recent public meeting with fans.
Oyston was heckled throughout over the way the club is being run.
"The owners of the club have received no approach whatsoever, from any investor or third party," said a statement.
The Blackpool Supporters Trust launched a £16m bid to buy the club July 2015 but Oyston, whose son Karl is chairman, eventually ended those takeover talks.
The Seasiders, who will play in the fourth tier for the first time since 2000-01 this season, have also announced the signing of midfielder Danny Pugh.
The 33-year-old former Manchester United trainee joins on a free transfer after his release by Bury and has signed a one-year deal, with further 12-month option.
"He brings a wealth of experience to the team and will be a strong, vocal presence in the middle of the park," said boss Gary Bowyer. | League Two club Blackpool have denied claims they were subject of a new takeover offer. | | The Cochrane Collaboration carried out a systematic review of eight exercise trials involving more than 300 patients living at home or in care.
Exercise did little for patients' moods, the research concluded.
But it did help them carry out daily activities such as rising from a chair, and boosted their cognitive skills.
Whether these benefits improve quality of life is still unclear, but the study authors say the findings are reason for optimism.
Dementia affects some 800,000 people in the UK. And the number of people with the condition is steadily increasing because people are living longer.
It is estimated that by 2021, the number of people with dementia in the UK will have increased to around one million.
With no cure, ways to improve the lives of those living with the condition are vital.
Researcher Dorothy Forbes, of the University of Alberta, and colleagues who carried out the Cochrane review, said: "Clearly, further research is needed to be able to develop best practice guidelines to enable healthcare providers to advise people with dementia living at home or in institutions.
"We also need to understand what level and intensity of exercise is beneficial for someone with dementia."
Dr Laura Phipps of Alzheimer's Research UK said: "We do know that exercise is an important part of keeping healthy, and though we can't say that exercise will prevent dementia, evidence does suggest it can help reduce the risk of the condition as part of a healthy lifestyle." | People with dementia who exercise improve their thinking abilities and everyday life, a body of medical research concludes. | * Loss: [CachedGISTEmbedLoss](https://sbert.net/docs/package_reference/sentence_transformer/losses.html#cachedgistembedloss) with these parameters: ```json {'guide': SentenceTransformer( (0): Transformer({'max_seq_length': 512, 'do_lower_case': False}) with Transformer model: BertModel (1): Pooling({'word_embedding_dimension': 768, 'pooling_mode_cls_token': True, 'pooling_mode_mean_tokens': False, 'pooling_mode_max_tokens': False, 'pooling_mode_mean_sqrt_len_tokens': False, 'pooling_mode_weightedmean_tokens': False, 'pooling_mode_lasttoken': False, 'include_prompt': True}) (2): Normalize() ), 'temperature': 0.05} ``` #### sciq_pairs * Dataset: [sciq_pairs](https://huggingface.co/datasets/allenai/sciq) at [2c94ad3](https://huggingface.co/datasets/allenai/sciq/tree/2c94ad3e1aafab77146f384e23536f97a4849815) * Size: 11,095 training samples * Columns: sentence1 and sentence2 * Approximate statistics based on the first 1000 samples: | | sentence1 | sentence2 | |:--------|:----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------| | type | string | string | | details | | | * Samples: | sentence1 | sentence2 | |:---------------------------------------------------------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------| | The bright color of poison dart frogs serves what purpose? | Poison dart frogs have toxins in their skin. Their bright colors warn potential predators not to take a bite!. | | What term describes motion that repeats itself at regular time intervals, such as exhibited by a vibrating guitar string? | When you pluck a guitar string, the resulting sound has a steady tone and lasts a long time. Each successive vibration of the string takes the same time as the previous one. We define periodic motion to be a motion that repeats itself at regular time intervals, such as exhibited by the guitar string or by an object on a spring moving up and down. The time to complete one oscillation remains constant and is called the period T . Its units are usually seconds, but may be any convenient unit of time. The word period refers to the time for some event whether repetitive or not; but we shall be primarily interested in periodic motion, which is by definition repetitive. A concept closely related to period is the frequency of an event. For example, if you get a paycheck twice a month, the frequency of payment is two per month and the period between checks is half a month. Frequency f is defined to be the number of events per unit time. For periodic motion, frequency is the number of oscillations per unit time. The relationship between frequency and period is. | | What do stored fats provide our body with for later use? | Fats are one type of lipid. Stored fat gives your body energy to use for later. It’s like having money in a savings account: it’s there in case you need it. Stored fat also cushions and protects internal organs. In addition, it insulates the body. It helps keep you warm in cold weather. | * Loss: [CachedGISTEmbedLoss](https://sbert.net/docs/package_reference/sentence_transformer/losses.html#cachedgistembedloss) with these parameters: ```json {'guide': SentenceTransformer( (0): Transformer({'max_seq_length': 512, 'do_lower_case': False}) with Transformer model: BertModel (1): Pooling({'word_embedding_dimension': 768, 'pooling_mode_cls_token': True, 'pooling_mode_mean_tokens': False, 'pooling_mode_max_tokens': False, 'pooling_mode_mean_sqrt_len_tokens': False, 'pooling_mode_weightedmean_tokens': False, 'pooling_mode_lasttoken': False, 'include_prompt': True}) (2): Normalize() ), 'temperature': 0.05} ``` #### qasc_pairs * Dataset: [qasc_pairs](https://huggingface.co/datasets/allenai/qasc) at [a34ba20](https://huggingface.co/datasets/allenai/qasc/tree/a34ba204eb9a33b919c10cc08f4f1c8dae5ec070) * Size: 7,727 training samples * Columns: sentence1 and sentence2 * Approximate statistics based on the first 1000 samples: | | sentence1 | sentence2 | |:--------|:---------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------| | type | string | string | | details | | | * Samples: | sentence1 | sentence2 | |:-------------------------------------------------------------------------|:-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------| | What do geologists use to determine the age of rock layers? | radioactive dating is used to determine the age of fossils. Geologists use fossils to determine the age of the rock layer that it was found in.. Geologists use radioactive dating to determine the age of rock layers. | | Air pollution can cause a decrease in what? | air pollution can cause the pH of soil to decrease. Research has shown that soil pH less than 6.0 can decrease crop yields.. Air pollution can cause a decrease in crop yields. | | What organism uses their sense of smell to find a mate? | Most salamanders use their sense of smell to find a mate.. Salamanders are a type of amphibian.. Some amphibians use their sense of smell to find a mate. | * Loss: [CachedGISTEmbedLoss](https://sbert.net/docs/package_reference/sentence_transformer/losses.html#cachedgistembedloss) with these parameters: ```json {'guide': SentenceTransformer( (0): Transformer({'max_seq_length': 512, 'do_lower_case': False}) with Transformer model: BertModel (1): Pooling({'word_embedding_dimension': 768, 'pooling_mode_cls_token': True, 'pooling_mode_mean_tokens': False, 'pooling_mode_max_tokens': False, 'pooling_mode_mean_sqrt_len_tokens': False, 'pooling_mode_weightedmean_tokens': False, 'pooling_mode_lasttoken': False, 'include_prompt': True}) (2): Normalize() ), 'temperature': 0.05} ``` #### openbookqa_pairs * Dataset: openbookqa_pairs * Size: 4,522 training samples * Columns: question and fact * Approximate statistics based on the first 1000 samples: | | question | fact | |:--------|:---------------------------------------------------------------------------------|:---------------------------------------------------------------------------------| | type | string | string | | details | | | * Samples: | question | fact | |:-----------------------------------------------------------------------------|:--------------------------------------------------------------------------------------| | What is animal competition? | if two animals eat the same prey then those animals compete for that pey | | If you wanted to make a metal bed frame, where would you start? | alloys are made of two or more metals | | Places lacking warmth have few what | cold environments contain few organisms | * Loss: [CachedGISTEmbedLoss](https://sbert.net/docs/package_reference/sentence_transformer/losses.html#cachedgistembedloss) with these parameters: ```json {'guide': SentenceTransformer( (0): Transformer({'max_seq_length': 512, 'do_lower_case': False}) with Transformer model: BertModel (1): Pooling({'word_embedding_dimension': 768, 'pooling_mode_cls_token': True, 'pooling_mode_mean_tokens': False, 'pooling_mode_max_tokens': False, 'pooling_mode_mean_sqrt_len_tokens': False, 'pooling_mode_weightedmean_tokens': False, 'pooling_mode_lasttoken': False, 'include_prompt': True}) (2): Normalize() ), 'temperature': 0.05} ``` #### msmarco_pairs * Dataset: [msmarco_pairs](https://huggingface.co/datasets/sentence-transformers/msmarco-msmarco-distilbert-base-v3) at [28ff31e](https://huggingface.co/datasets/sentence-transformers/msmarco-msmarco-distilbert-base-v3/tree/28ff31e4c97cddd53d298497f766e653f1e666f9) * Size: 30,250 training samples * Columns: sentence1 and sentence2 * Approximate statistics based on the first 1000 samples: | | sentence1 | sentence2 | |:--------|:---------------------------------------------------------------------------------|:------------------------------------------------------------------------------------| | type | string | string | | details | | | * Samples: | sentence1 | sentence2 | |:---------------------------------------------------|:------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------| | propria definition | The lamina propria is a constituent of the moist linings known as mucous membranes or mucosa, which line various tubes in the body.The lamina propria is a thin layer of loose connective tissue which lies beneath the epithelium and together with the epithelium constitutes the mucosa.As its Latin name indicates it is a characteristic component of the mucosa, the mucosa's own special layer.he lamina propria is a constituent of the moist linings known as mucous membranes or mucosa, which line various tubes in the body. | | what family is the common bullfrog in | The American bullfrog (Rana catesbeiana), often simply known as the bullfrog in Canada and the United States, is an aquatic frog, a member of the family Ranidae, or “true frogs”. This frog has an olive green back and sides blotched with brownish markings and a whitish belly spotted with yellow or grey. | | why does well pump cycle on and off | 1 When a well pump turns on every time a water-using fixture’s valve is opened, or if it turns on and off rapidly while the fixture is in use, that’s short cycling. It is typically caused by a water pressure tank that has lost it built-in cushion of pressurized air. | * Loss: [CachedGISTEmbedLoss](https://sbert.net/docs/package_reference/sentence_transformer/losses.html#cachedgistembedloss) with these parameters: ```json {'guide': SentenceTransformer( (0): Transformer({'max_seq_length': 512, 'do_lower_case': False}) with Transformer model: BertModel (1): Pooling({'word_embedding_dimension': 768, 'pooling_mode_cls_token': True, 'pooling_mode_mean_tokens': False, 'pooling_mode_max_tokens': False, 'pooling_mode_mean_sqrt_len_tokens': False, 'pooling_mode_weightedmean_tokens': False, 'pooling_mode_lasttoken': False, 'include_prompt': True}) (2): Normalize() ), 'temperature': 0.05} ``` #### nq_pairs * Dataset: [nq_pairs](https://huggingface.co/datasets/sentence-transformers/natural-questions) at [f9e894e](https://huggingface.co/datasets/sentence-transformers/natural-questions/tree/f9e894e1081e206e577b4eaa9ee6de2b06ae6f17) * Size: 30,250 training samples * Columns: sentence1 and sentence2 * Approximate statistics based on the first 1000 samples: | | sentence1 | sentence2 | |:--------|:-----------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------| | type | string | string | | details | | | * Samples: | sentence1 | sentence2 | |:-----------------------------------------------------------------------------|:-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------| | who established the republic of china in 1912 ce | Republic of China (1912–1949) The Republic of China was a sovereign state in East Asia, that occupied the territories of modern China and for part of its history Mongolia and Taiwan. It was founded in 1912, after the Qing dynasty, the last imperial dynasty, was overthrown in the Xinhai Revolution. The Republic's first president, Sun Yat-sen, served only briefly before handing over the position to Yuan Shikai, former leader of the Beiyang Army. His party, then led by Song Jiaoren, won the parliamentary election held in December 1912. Song was assassinated shortly after, and the Beiyang Army led by Yuan Shikai maintained full control of the government in Beijing. Between late 1915 and early 1916, Yuan tried to reinstate the monarchy, before resigning after popular unrest. After Yuan's death in 1916, members of cliques in the former Beiyang Army claimed their autonomy and clashed with each other. During this period, the authority of the republican government was weakened by a restoration of the Qing government. | | what is the message in john lennon's imagine | Imagine (John Lennon song) "Imagine" is a song written and performed by English musician John Lennon. The best-selling single of his solo career, its lyrics encourage the listener to imagine a world at peace without the barriers of borders or the divisions of religion and nationality, and to consider the possibility that the whole of humanity would live unattached to material possessions. | | who is the original singer for these boots are made for walking | These Boots Are Made for Walkin' "These Boots Are Made for Walkin'" is a hit song written by Lee Hazlewood and recorded by Nancy Sinatra. It charted January 22, 1966,[3] and reached No. 1 in the United States Billboard Hot 100 and in the UK Singles Chart.[2] | * Loss: [CachedGISTEmbedLoss](https://sbert.net/docs/package_reference/sentence_transformer/losses.html#cachedgistembedloss) with these parameters: ```json {'guide': SentenceTransformer( (0): Transformer({'max_seq_length': 512, 'do_lower_case': False}) with Transformer model: BertModel (1): Pooling({'word_embedding_dimension': 768, 'pooling_mode_cls_token': True, 'pooling_mode_mean_tokens': False, 'pooling_mode_max_tokens': False, 'pooling_mode_mean_sqrt_len_tokens': False, 'pooling_mode_weightedmean_tokens': False, 'pooling_mode_lasttoken': False, 'include_prompt': True}) (2): Normalize() ), 'temperature': 0.05} ``` #### trivia_pairs * Dataset: [trivia_pairs](https://huggingface.co/datasets/sentence-transformers/trivia-qa) at [a7c36e3](https://huggingface.co/datasets/sentence-transformers/trivia-qa/tree/a7c36e3c8c8c01526bc094d79bf80d4c848b0ad0) * Size: 12,024 training samples * Columns: query and answer * Approximate statistics based on the first 1000 samples: | | query | answer | |:--------|:----------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------| | type | string | string | | details | | | * Samples: | query | answer | |:--------------------------------------------------------------------------------------------------------|:----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------| | What is the name of 'Bob the Builder's' cement mixer? | BOB the BUILDER DIZZY the CEMENT MIXER BOB the BUILDER DIZZY THE CEMENT MIXER Large Friction Action Dizzy the Cement Mixer and clicky noise turn by hand Mixer from the Large Bob The Builder Friction toy Collection  Measures 5" x  4" High  in EXCELLENT Played with Condition �8.00 .. US $15.60  .. EUROS 12.00 Ref # 0845 | | Which cartoon character, who cooks at the Krusty Krab, lives in a pineapple under the sea? | SpongeBob SquarePants from SpongeBob SquarePants| Cartoon | Nick.com Gary SpongeBob SquarePants Come follow the adventures of the world's most lovable sponge and his starfish sidekick! Though they have the best intentions, SpongeBob and Patrick are always causing trouble… and plenty of laughs! When he's not at the Krusty Krab grilling up some epic Krabby Patties, SpongeBob can be found jellyfishing with Patrick, blowing bubbles, or annoying his favorite neighbor, Squidward! Bikini Bottom is home to the coolest creatures under the sea, and you CAN'T miss out on any of their adventures. Is mayonnaise an instrument? Watch SpongeBob SquarePants to find out! Are you ready, kids? AYE AYE CAPTAIN! ON TV | | Chinese Democracy was the long awaited 2008 album release of which band? | Guns N Roses 'Chinese Democracy' Set For Wal-Mart Release | Gigwise Guns N Roses 'Chinese Democracy' Set For Wal-Mart Release Band are in talks... Guns N Roses Tickets Buy tickets safely & securely with Seatwave Guns N’ Roses long-awaited new studio album could be released exclusively in retail stores, it’s been reported. Wal-Mart and Best Buy are understood to be leading negotiations to acquire 'Chinese Democracy's' release - possibly before the end of 2008. Industry reports have escalated since Irving Azoff's Front Line Management took over all of the bands business duties. Last year, the company were influential in instigating the release of The Eagles ‘Long Road To Eden’ via Wal-Mart chains. The album enjoyed huge, chart-topping success in the US. According to Billboard, Guns N Roses are also in negotiations for a more traditional release which would take in the rest of the world. As previously reported on Gigwise , Guns N Roses will release their first song in over a decade on the next installment of Rock Band. 'Shackler's Revenge' leads a playlist that spans music releases from the 1960s to today. Guns N Roses – Through The Years. | * Loss: [CachedGISTEmbedLoss](https://sbert.net/docs/package_reference/sentence_transformer/losses.html#cachedgistembedloss) with these parameters: ```json {'guide': SentenceTransformer( (0): Transformer({'max_seq_length': 512, 'do_lower_case': False}) with Transformer model: BertModel (1): Pooling({'word_embedding_dimension': 768, 'pooling_mode_cls_token': True, 'pooling_mode_mean_tokens': False, 'pooling_mode_max_tokens': False, 'pooling_mode_mean_sqrt_len_tokens': False, 'pooling_mode_weightedmean_tokens': False, 'pooling_mode_lasttoken': False, 'include_prompt': True}) (2): Normalize() ), 'temperature': 0.05} ``` #### gooaq_pairs * Dataset: [gooaq_pairs](https://huggingface.co/datasets/sentence-transformers/gooaq) at [b089f72](https://huggingface.co/datasets/sentence-transformers/gooaq/tree/b089f728748a068b7bc5234e5bcf5b25e3c8279c) * Size: 30,250 training samples * Columns: sentence1 and sentence2 * Approximate statistics based on the first 1000 samples: | | sentence1 | sentence2 | |:--------|:----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------| | type | string | string | | details | | | * Samples: | sentence1 | sentence2 | |:------------------------------------------------------|:------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------| | do namibians need a visa for london? | The Embassy is closed every Friday. Namibia tourist visa is not required for citizens of United Kingdom for a stay up to 90 days. Sounds good! | | what is the meaning of personal finance? | Personal finance is a term that covers managing your money as well as saving and investing. ... It often refers to the entire industry that provides financial services to individuals and households and advises them about financial and investment opportunities. | | what are trim tabs for? | Trim tabs are either flat plates or vertical blades fitted either side of the boat and attached to the transom. They are used to trim or level the boat, both fore and aft and side to side. Trim tabs are controlled up and downwards by either a hydraulic, or electric ram system on the transom. | * Loss: [CachedGISTEmbedLoss](https://sbert.net/docs/package_reference/sentence_transformer/losses.html#cachedgistembedloss) with these parameters: ```json {'guide': SentenceTransformer( (0): Transformer({'max_seq_length': 512, 'do_lower_case': False}) with Transformer model: BertModel (1): Pooling({'word_embedding_dimension': 768, 'pooling_mode_cls_token': True, 'pooling_mode_mean_tokens': False, 'pooling_mode_max_tokens': False, 'pooling_mode_mean_sqrt_len_tokens': False, 'pooling_mode_weightedmean_tokens': False, 'pooling_mode_lasttoken': False, 'include_prompt': True}) (2): Normalize() ), 'temperature': 0.05} ``` #### paws-pos * Dataset: [paws-pos](https://huggingface.co/datasets/google-research-datasets/paws) at [161ece9](https://huggingface.co/datasets/google-research-datasets/paws/tree/161ece9501cf0a11f3e48bd356eaa82de46d6a09) * Size: 21,829 training samples * Columns: sentence1 and sentence2 * Approximate statistics based on the first 1000 samples: | | sentence1 | sentence2 | |:--------|:----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------| | type | string | string | | details | | | * Samples: | sentence1 | sentence2 | |:-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------| | Thompson was born in Hendon , North London , Dena Holmes in 1960 and worked for a building society bank . | Thompson was born Dena Holmes in 1960 in Hendon , North London . She worked for a building society . | | One of his first cousins was Elizabeth , aka Lady Elizabeth Hervey , aka Bess Foster , Duchess of Devonshire . His younger brother married Lord Bishop Foster . | One of his first cousins was Elizabeth , alias Lady Elizabeth Hervey , alias Bess Foster , Duchess of Devonshire , his younger brother married Lord Bishop Foster . | | At the executive level , EEAA represents the central arm of the Ministry . | At executive level , EEAA represents the central arm of the ministry . | * Loss: [CachedGISTEmbedLoss](https://sbert.net/docs/package_reference/sentence_transformer/losses.html#cachedgistembedloss) with these parameters: ```json {'guide': SentenceTransformer( (0): Transformer({'max_seq_length': 512, 'do_lower_case': False}) with Transformer model: BertModel (1): Pooling({'word_embedding_dimension': 768, 'pooling_mode_cls_token': True, 'pooling_mode_mean_tokens': False, 'pooling_mode_max_tokens': False, 'pooling_mode_mean_sqrt_len_tokens': False, 'pooling_mode_weightedmean_tokens': False, 'pooling_mode_lasttoken': False, 'include_prompt': True}) (2): Normalize() ), 'temperature': 0.05} ``` ### Evaluation Datasets #### vitaminc-pairs * Dataset: [vitaminc-pairs](https://huggingface.co/datasets/tals/vitaminc) at [be6febb](https://huggingface.co/datasets/tals/vitaminc/tree/be6febb761b0b2807687e61e0b5282e459df2fa0) * Size: 108 evaluation samples * Columns: claim and evidence * Approximate statistics based on the first 1000 samples: | | claim | evidence | |:--------|:----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------| | type | string | string | | details | | | * Samples: | claim | evidence | |:------------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------| | Dragon Con had over 5000 guests . | Among the more than 6000 guests and musical performers at the 2009 convention were such notables as Patrick Stewart , William Shatner , Leonard Nimoy , Terry Gilliam , Bruce Boxleitner , James Marsters , and Mary McDonnell . | | COVID-19 has reached more than 185 countries . | As of , more than cases of COVID-19 have been reported in more than 190 countries and 200 territories , resulting in more than deaths . | | In March , Italy had 3.6x times more cases of coronavirus than China . | As of 12 March , among nations with at least one million citizens , Italy has the world 's highest per capita rate of positive coronavirus cases at 206.1 cases per million people ( 3.6x times the rate of China ) and is the country with the second-highest number of positive cases as well as of deaths in the world , after China . | * Loss: [CachedGISTEmbedLoss](https://sbert.net/docs/package_reference/sentence_transformer/losses.html#cachedgistembedloss) with these parameters: ```json {'guide': SentenceTransformer( (0): Transformer({'max_seq_length': 512, 'do_lower_case': False}) with Transformer model: BertModel (1): Pooling({'word_embedding_dimension': 768, 'pooling_mode_cls_token': True, 'pooling_mode_mean_tokens': False, 'pooling_mode_max_tokens': False, 'pooling_mode_mean_sqrt_len_tokens': False, 'pooling_mode_weightedmean_tokens': False, 'pooling_mode_lasttoken': False, 'include_prompt': True}) (2): Normalize() ), 'temperature': 0.05} ``` #### negation-triplets * Dataset: negation-triplets * Size: 64 evaluation samples * Columns: anchor, entailment, and negative * Approximate statistics based on the first 1000 samples: | | anchor | entailment | negative | |:--------|:-----------------------------------------------------------------------------------|:----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------| | type | string | string | string | | details | | | | * Samples: | anchor | entailment | negative | |:---------------------------------------------------------------------------------|:-----------------------------------------------------------------------|:-----------------------------------------------------------------| | Set of toy animals sitting in front of a red wooden wagon. | Several toy animals - a bull, giraffe, deer and parakeet. | Several toy animals - a cow, lion, wolf and canary. | | A bathroom with a toilette with it's seat down. | A bathroom with a sink and a toilet | A bathroom without a sink or a toilet | | A striped plane flying up into the sky as the sun shines behind it. | An airplane is ascending into the white sky | An airplane is descending into the black sky | * Loss: [CachedGISTEmbedLoss](https://sbert.net/docs/package_reference/sentence_transformer/losses.html#cachedgistembedloss) with these parameters: ```json {'guide': SentenceTransformer( (0): Transformer({'max_seq_length': 512, 'do_lower_case': False}) with Transformer model: BertModel (1): Pooling({'word_embedding_dimension': 768, 'pooling_mode_cls_token': True, 'pooling_mode_mean_tokens': False, 'pooling_mode_max_tokens': False, 'pooling_mode_mean_sqrt_len_tokens': False, 'pooling_mode_weightedmean_tokens': False, 'pooling_mode_lasttoken': False, 'include_prompt': True}) (2): Normalize() ), 'temperature': 0.05} ``` #### scitail-pairs-pos * Dataset: [scitail-pairs-pos](https://huggingface.co/datasets/allenai/scitail) at [0cc4353](https://huggingface.co/datasets/allenai/scitail/tree/0cc4353235b289165dfde1c7c5d1be983f99ce44) * Size: 54 evaluation samples * Columns: sentence1 and sentence2 * Approximate statistics based on the first 1000 samples: | | sentence1 | sentence2 | |:--------|:----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------| | type | string | string | | details | | | * Samples: | sentence1 | sentence2 | |:----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:---------------------------------------------------------------------------------------| | humans normally have 23 pairs of chromosomes. | Humans typically have 23 pairs pairs of chromosomes. | | A solution is a homogenous mixture of two or more substances that exist in a single phase. | Solution is the term for a homogeneous mixture of two or more substances. | | Upwelling The physical process in near-shore ocean systems of rising of nutrients and colder bottom waters to the surface because of constant wind patterns along the shoreline. | Upwelling is the term for when deep ocean water rises to the surface. | * Loss: [CachedGISTEmbedLoss](https://sbert.net/docs/package_reference/sentence_transformer/losses.html#cachedgistembedloss) with these parameters: ```json {'guide': SentenceTransformer( (0): Transformer({'max_seq_length': 512, 'do_lower_case': False}) with Transformer model: BertModel (1): Pooling({'word_embedding_dimension': 768, 'pooling_mode_cls_token': True, 'pooling_mode_mean_tokens': False, 'pooling_mode_max_tokens': False, 'pooling_mode_mean_sqrt_len_tokens': False, 'pooling_mode_weightedmean_tokens': False, 'pooling_mode_lasttoken': False, 'include_prompt': True}) (2): Normalize() ), 'temperature': 0.05} ``` #### scitail-pairs-qa * Dataset: [scitail-pairs-qa](https://huggingface.co/datasets/allenai/scitail) at [0cc4353](https://huggingface.co/datasets/allenai/scitail/tree/0cc4353235b289165dfde1c7c5d1be983f99ce44) * Size: 128 evaluation samples * Columns: sentence2 and question * Approximate statistics based on the first 1000 samples: | | sentence2 | question | |:--------|:----------------------------------------------------------------------------------|:----------------------------------------------------------------------------------| | type | string | string | | details | | | * Samples: | sentence2 | question | |:---------------------------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------| | It takes earth one week to rotate on its axis seven times. | How long does it take for Earth to rotate on its axis seven times? | | Both hurricanes and tornadoes always have high winds. | Both hurricanes and tornadoes always | | Seeds of a pine cone are easily carried by the wind and dispersed because seeds have wings. | Why are seeds of a pine cone easily carried by the wind and dispersed? | * Loss: [CachedGISTEmbedLoss](https://sbert.net/docs/package_reference/sentence_transformer/losses.html#cachedgistembedloss) with these parameters: ```json {'guide': SentenceTransformer( (0): Transformer({'max_seq_length': 512, 'do_lower_case': False}) with Transformer model: BertModel (1): Pooling({'word_embedding_dimension': 768, 'pooling_mode_cls_token': True, 'pooling_mode_mean_tokens': False, 'pooling_mode_max_tokens': False, 'pooling_mode_mean_sqrt_len_tokens': False, 'pooling_mode_weightedmean_tokens': False, 'pooling_mode_lasttoken': False, 'include_prompt': True}) (2): Normalize() ), 'temperature': 0.05} ``` #### xsum-pairs * Dataset: xsum-pairs * Size: 128 evaluation samples * Columns: document and summary * Approximate statistics based on the first 1000 samples: | | document | summary | |:--------|:-------------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------| | type | string | string | | details | | | * Samples: | document | summary | |:-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------------------------------------------| | The rescue on Monday afternoon involved a challenging winch down to the casualty by a coastguard helicopter's paramedic.
The Inverness Airport-based helicopter could not be brought too close in case its downdraft blew the man and his fellow walkers off the ridge.
The walker was taken to hospital for treatment.
The alarm was raised at 14:25 on Monday after the man became unwell on Carn Mor Dearg.
He was airlifted to Torlundy and from there was taken to hospital by ambulance.
Scott Sharman, paramedic winchman, said: "It was an extremely steep ridge and we needed to make sure we kept at a safe distance because the downdraft could very easily have blown them over the ridge." | A walker had to be rescued from a 1,000m (3,500ft) ridge near Ben Nevis after he became ill. | | The 23-year-old, who did not make a senior appearances during a year with the Hornets, has signed a two-year deal with the O's.
Woods began his career in Cambridge United's youth set-up and subsequently joined Manchester United's academy.
He moved to Doncaster Rovers in 2009 and went on to make 82 appearances, before leaving the club last summer.
Woods, a former England Under-19 international, will provide competition for fellow new arrival Adam Legzdins. | League One side Leyton Orient have signed goalkeeper Gary Woods following his departure from Watford. | | The 32-year-old, the number one ranked Test bowler, has been out of action with a groin strain since the first Test against India in early November.
But in Cape Town this week he was able to complete two bowling spells at match intensity in the nets, run sprints and do agility tests and fielding drills.
The first of the four-match Test series begins in Durban on 26 December.
Proteas team manager, Dr Mohammed Moosajee said: "Dale has put a lot of work into his training and rehab since his return from India so we are very happy to have him back from injury.
"He was put through a thorough fitness test on Thursday by physiotherapist, Shane Jabaar, he came through the tests without any discomfort and will be available for selection for the first Test match against England."
Steyn has taken 402 wickets in 81 Tests at an average of 22.56, including 46 in 11 matches against England.
South Africa remain at the top of the Test rankings despite a 3-0 defeat in India this month. | South Africa paceman Dale Steyn will be fit for the Test series with England after passing a fitness test. | * Loss: [CachedGISTEmbedLoss](https://sbert.net/docs/package_reference/sentence_transformer/losses.html#cachedgistembedloss) with these parameters: ```json {'guide': SentenceTransformer( (0): Transformer({'max_seq_length': 512, 'do_lower_case': False}) with Transformer model: BertModel (1): Pooling({'word_embedding_dimension': 768, 'pooling_mode_cls_token': True, 'pooling_mode_mean_tokens': False, 'pooling_mode_max_tokens': False, 'pooling_mode_mean_sqrt_len_tokens': False, 'pooling_mode_weightedmean_tokens': False, 'pooling_mode_lasttoken': False, 'include_prompt': True}) (2): Normalize() ), 'temperature': 0.05} ``` #### sciq_pairs * Dataset: [sciq_pairs](https://huggingface.co/datasets/allenai/sciq) at [2c94ad3](https://huggingface.co/datasets/allenai/sciq/tree/2c94ad3e1aafab77146f384e23536f97a4849815) * Size: 128 evaluation samples * Columns: sentence1 and sentence2 * Approximate statistics based on the first 1000 samples: | | sentence1 | sentence2 | |:--------|:----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------| | type | string | string | | details | | | * Samples: | sentence1 | sentence2 | |:--------------------------------------------------------------------------------------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------| | The skull is a part of a vertebrate endoskeleton that encloses and protects what organ? | part of a vertebrate endoskeleton that encloses and protects the brain; also called the skull. | | The action of sunlight on the skin triggers the body to produce what vitamin? | Milk and other dairy foods are not the only sources of calcium. This important nutrient is also found in green leafy vegetables, broccoli, and intact salmon and canned sardines with their soft bones. Nuts, beans, seeds, and shellfish provide calcium in smaller quantities. Except for fatty fish like salmon and tuna, or fortified milk or cereal, vitamin D is not found naturally in many foods. The action of sunlight on the skin triggers the body to produce its own vitamin D (Figure 6.22), but many people, especially those of darker complexion and those living in northern latitudes where the sun’s rays are not as strong, are deficient in vitamin D. In cases of deficiency, a doctor can prescribe a vitamin D supplement. | | What phenomenon is essential in order for evolution to occur because it increases genetic variation and the potential for individuals to differ? | Mutations are essential for evolution to occur because they increase genetic variation and the potential for individuals to differ. The majority of mutations are neutral in their effects on the organisms in which they occur. Beneficial mutations may become more common through natural selection. Harmful mutations may cause genetic disorders or cancer. | * Loss: [CachedGISTEmbedLoss](https://sbert.net/docs/package_reference/sentence_transformer/losses.html#cachedgistembedloss) with these parameters: ```json {'guide': SentenceTransformer( (0): Transformer({'max_seq_length': 512, 'do_lower_case': False}) with Transformer model: BertModel (1): Pooling({'word_embedding_dimension': 768, 'pooling_mode_cls_token': True, 'pooling_mode_mean_tokens': False, 'pooling_mode_max_tokens': False, 'pooling_mode_mean_sqrt_len_tokens': False, 'pooling_mode_weightedmean_tokens': False, 'pooling_mode_lasttoken': False, 'include_prompt': True}) (2): Normalize() ), 'temperature': 0.05} ``` #### qasc_pairs * Dataset: [qasc_pairs](https://huggingface.co/datasets/allenai/qasc) at [a34ba20](https://huggingface.co/datasets/allenai/qasc/tree/a34ba204eb9a33b919c10cc08f4f1c8dae5ec070) * Size: 128 evaluation samples * Columns: sentence1 and sentence2 * Approximate statistics based on the first 1000 samples: | | sentence1 | sentence2 | |:--------|:----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------| | type | string | string | | details | | | * Samples: | sentence1 | sentence2 | |:----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------| | What designed for swimming are used for moving faster through water? | webbed feet are used for moving faster through water by aquatic animals. Ducks have webbed feet, designed for swimming.. Feet designed for swimming are used for moving faster through water. | | what falls making sunlight available to surrounding plants? | if a tree falls then sunlight becomes available to the surrounding plants. Oak trees are found throughout.. if an oak falls then sunlight becomes available to surrounding plants | | What is the term used for an individual who is learning ethology? | Ethologists usually study how animals behave in their natural environment.. Ethology is the study of behavior.. Ethologists learn ethology | * Loss: [CachedGISTEmbedLoss](https://sbert.net/docs/package_reference/sentence_transformer/losses.html#cachedgistembedloss) with these parameters: ```json {'guide': SentenceTransformer( (0): Transformer({'max_seq_length': 512, 'do_lower_case': False}) with Transformer model: BertModel (1): Pooling({'word_embedding_dimension': 768, 'pooling_mode_cls_token': True, 'pooling_mode_mean_tokens': False, 'pooling_mode_max_tokens': False, 'pooling_mode_mean_sqrt_len_tokens': False, 'pooling_mode_weightedmean_tokens': False, 'pooling_mode_lasttoken': False, 'include_prompt': True}) (2): Normalize() ), 'temperature': 0.05} ``` #### openbookqa_pairs * Dataset: openbookqa_pairs * Size: 128 evaluation samples * Columns: question and fact * Approximate statistics based on the first 1000 samples: | | question | fact | |:--------|:----------------------------------------------------------------------------------|:----------------------------------------------------------------------------------| | type | string | string | | details | | | * Samples: | question | fact | |:-----------------------------------------------------------------------|:-----------------------------------------------------------------------------| | The thermal production of a stove is generically used for | a stove generates heat for cooking usually | | What creates a valley? | a valley is formed by a river flowing | | when it turns day and night on a planet, what cause this? | a planet rotating causes cycles of day and night on that planet | * Loss: [CachedGISTEmbedLoss](https://sbert.net/docs/package_reference/sentence_transformer/losses.html#cachedgistembedloss) with these parameters: ```json {'guide': SentenceTransformer( (0): Transformer({'max_seq_length': 512, 'do_lower_case': False}) with Transformer model: BertModel (1): Pooling({'word_embedding_dimension': 768, 'pooling_mode_cls_token': True, 'pooling_mode_mean_tokens': False, 'pooling_mode_max_tokens': False, 'pooling_mode_mean_sqrt_len_tokens': False, 'pooling_mode_weightedmean_tokens': False, 'pooling_mode_lasttoken': False, 'include_prompt': True}) (2): Normalize() ), 'temperature': 0.05} ``` #### msmarco_pairs * Dataset: [msmarco_pairs](https://huggingface.co/datasets/sentence-transformers/msmarco-msmarco-distilbert-base-v3) at [28ff31e](https://huggingface.co/datasets/sentence-transformers/msmarco-msmarco-distilbert-base-v3/tree/28ff31e4c97cddd53d298497f766e653f1e666f9) * Size: 128 evaluation samples * Columns: sentence1 and sentence2 * Approximate statistics based on the first 1000 samples: | | sentence1 | sentence2 | |:--------|:---------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------| | type | string | string | | details | | | * Samples: | sentence1 | sentence2 | |:-------------------------------------------------------------|:-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------| | when did young american by david bowie come out | Young Americans (song) Young Americans is a single by English singer and songwriter David Bowie, released in 1975. It is included in the album of the same name. The song was a massive breakthrough in the United States, where glam rock had never really become very popular outside the major cities. | | are investment commissions tax deductible | You typically pay a commission when you buy, and you pay another commission when you sell. The IRS does not consider investment commissions to be a tax-deductible expense. Instead, the commission becomes part of the investment's cost basis, which still provides you with some tax relief. | | does photosynthesis occur in prokaryotes | Animal cells do not undergo photosynthesis, but in a plant cell, the site of photosynthesis is the chloroplast. Prokaryotes are more primitive-they have no nucleus for a start, and also have no chloroplasts.They are bacterial cells and so do not undergo photosynthesis.ating Newest Oldest. Best Answer: Actually, some procaryotes have photosynthesis. The thing is, as they don't have organelles, it doesn't occur in a differentiated structure, like choroplasts in eucaryotes. It happens along the plasma membrane. | * Loss: [CachedGISTEmbedLoss](https://sbert.net/docs/package_reference/sentence_transformer/losses.html#cachedgistembedloss) with these parameters: ```json {'guide': SentenceTransformer( (0): Transformer({'max_seq_length': 512, 'do_lower_case': False}) with Transformer model: BertModel (1): Pooling({'word_embedding_dimension': 768, 'pooling_mode_cls_token': True, 'pooling_mode_mean_tokens': False, 'pooling_mode_max_tokens': False, 'pooling_mode_mean_sqrt_len_tokens': False, 'pooling_mode_weightedmean_tokens': False, 'pooling_mode_lasttoken': False, 'include_prompt': True}) (2): Normalize() ), 'temperature': 0.05} ``` #### nq_pairs * Dataset: [nq_pairs](https://huggingface.co/datasets/sentence-transformers/natural-questions) at [f9e894e](https://huggingface.co/datasets/sentence-transformers/natural-questions/tree/f9e894e1081e206e577b4eaa9ee6de2b06ae6f17) * Size: 128 evaluation samples * Columns: sentence1 and sentence2 * Approximate statistics based on the first 1000 samples: | | sentence1 | sentence2 | |:--------|:-----------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------| | type | string | string | | details | | | * Samples: | sentence1 | sentence2 | |:--------------------------------------------------------------|:--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------| | who played gimli in the lord of the rings movies | John Rhys-Davies John Rhys-Davies (born 5 May 1944) is a Welsh actor and voice actor known for his portrayal of Gimli in The Lord of the Rings trilogy and the charismatic Arab excavator Sallah in the Indiana Jones films. He also played Agent Michael Malone in the 1993 remake of the 1950s television series The Untouchables, Pilot Vasco Rodrigues in the mini-series Shōgun, Professor Maximillian Arturo in Sliders, King Richard I in Robin of Sherwood, General Leonid Pushkin in the James Bond film The Living Daylights, and Macro in I, Claudius. Additionally, he provided the voices of Cassim in Disney's Aladdin and the King of Thieves, Macbeth in Gargoyles, Man Ray in SpongeBob SquarePants, Hades in Justice League and Tobias in the computer game Freelancer. | | why did the red sea get its name | Red Sea Red Sea is a direct translation of the Greek Erythra Thalassa (Ερυθρὰ Θάλασσα), Latin Mare Rubrum (alternatively Sinus Arabicus, literally "Arabian Gulf"), Arabic: البحر الأحمر‎, translit. Al-Baḥr Al-Aḥmar (alternatively بحر القلزم Baḥr Al-Qulzum, literally "the Sea of Clysma"), Somali Badda Cas and Tigrinya Qeyyiḥ bāḥrī (ቀይሕ ባሕሪ). The name of the sea may signify the seasonal blooms of the red-coloured Trichodesmium erythraeum near the water's surface.[5] A theory favored by some modern scholars is that the name red is referring to the direction south, just as the Black Sea's name may refer to north. The basis of this theory is that some Asiatic languages used color words to refer to the cardinal directions.[6] Herodotus on one occasion uses Red Sea and Southern Sea interchangeably.[7] | | when is the new president of mexico announced | Mexican general election, 2018 López Obrador won the election on 1 July 2018 with over 50% of the popular vote. In terms of states won, López Obrador won in a landslide, carrying 31 out of 32 of the country's states,[5] the most states won by a candidate since Ernesto Zedillo won every state in the 1994 election. | * Loss: [CachedGISTEmbedLoss](https://sbert.net/docs/package_reference/sentence_transformer/losses.html#cachedgistembedloss) with these parameters: ```json {'guide': SentenceTransformer( (0): Transformer({'max_seq_length': 512, 'do_lower_case': False}) with Transformer model: BertModel (1): Pooling({'word_embedding_dimension': 768, 'pooling_mode_cls_token': True, 'pooling_mode_mean_tokens': False, 'pooling_mode_max_tokens': False, 'pooling_mode_mean_sqrt_len_tokens': False, 'pooling_mode_weightedmean_tokens': False, 'pooling_mode_lasttoken': False, 'include_prompt': True}) (2): Normalize() ), 'temperature': 0.05} ``` #### trivia_pairs * Dataset: [trivia_pairs](https://huggingface.co/datasets/sentence-transformers/trivia-qa) at [a7c36e3](https://huggingface.co/datasets/sentence-transformers/trivia-qa/tree/a7c36e3c8c8c01526bc094d79bf80d4c848b0ad0) * Size: 128 evaluation samples * Columns: query and answer * Approximate statistics based on the first 1000 samples: | | query | answer | |:--------|:----------------------------------------------------------------------------------|:-------------------------------------------------------------------------------------| | type | string | string | | details | | | * Samples: | query | answer | |:----------------------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------| | Who sang '99 Red Balloons'? | 99 red ballons - Nena - YouTube 99 red ballons - Nena Want to watch this again later? Sign in to add this video to a playlist. Need to report the video? Sign in to report inappropriate content. Rating is available when the video has been rented. This feature is not available right now. Please try again later. Uploaded on Jul 29, 2006 This is the video 99 red ballons (english version) by nena Category | | Who is the patron saint of doctors, surgeons, painters and artists? | St. Luke Medals St. Luke Medals St. Luke is the Patron Saint of artists, brewers, butchers, doctors, glassworks, painters, physicians and surgeons. Luke is symbolically portrayed as an animal of sacrifice, the ox, because he begins his Gospel with the history of Zachary, the priest offering sacrifice to God, and because throughout his Gospel he accentuates the universal priesthood of Christ. St. Luke�s Gospel includes six miracles and 18 parables not found elsewhere in the Bible. | | Vande Mataram (I praise thee, Mother) is the national song of which BRIC nation? | 'Vande Mataram' Real National Anthem: RSS Leader- The New Indian Express 'Vande Mataram' Real National Anthem: RSS Leader By PTI   |   Published: 02nd April 2016 01:09 PM  |   Last Updated: 02nd April 2016 01:09 PM  |   A+A A-   |   0 Share Via Email MUMBAI: Days after RSS chief Mohan Bhagwat's 'Bharat Mata Ki Jai' remarks, a top functionary of the organisation has said that 'Vande Mataram' is the real national anthem as opposed to the 'Constitutionally-mandated' Jana Gana Mana. "Jana Gana Mana is today our national anthem. It has to be respected. There is no reason why it should evoke any other sentiment," RSS General Secretary Bhaiyyaji Joshi said. "But it is the national anthem as decided by the Constitution. If one considers the true meaning, then Vande Mataram is the national anthem," he said yesterday at the Deendayal Upadhyay Research Institute here. "We consider things created due to the Constitution to be national," Joshi said. "When was Jana Gana Mana written? It was written some time back. But the sentiments expressed in Jana Gana Mana have been expressed keeping the state in view," he said. "However, the sentiments expressed in Vande Mataram denote the nation's character and style. This is the difference between the two songs. Both deserve respect," Joshi said. 'Vande Mataram', literally, "I praise thee, Mother", is a poem by Bankim Chandra Chattopadhyay. A hymn to the 'Mother Land', it played a vital role in the Indian independence movement. In 1950, the song's first two verses were given the official status of the "national song", distinct from the national anthem, Jana Gana Mana. O | * Loss: [CachedGISTEmbedLoss](https://sbert.net/docs/package_reference/sentence_transformer/losses.html#cachedgistembedloss) with these parameters: ```json {'guide': SentenceTransformer( (0): Transformer({'max_seq_length': 512, 'do_lower_case': False}) with Transformer model: BertModel (1): Pooling({'word_embedding_dimension': 768, 'pooling_mode_cls_token': True, 'pooling_mode_mean_tokens': False, 'pooling_mode_max_tokens': False, 'pooling_mode_mean_sqrt_len_tokens': False, 'pooling_mode_weightedmean_tokens': False, 'pooling_mode_lasttoken': False, 'include_prompt': True}) (2): Normalize() ), 'temperature': 0.05} ``` #### gooaq_pairs * Dataset: [gooaq_pairs](https://huggingface.co/datasets/sentence-transformers/gooaq) at [b089f72](https://huggingface.co/datasets/sentence-transformers/gooaq/tree/b089f728748a068b7bc5234e5bcf5b25e3c8279c) * Size: 128 evaluation samples * Columns: sentence1 and sentence2 * Approximate statistics based on the first 1000 samples: | | sentence1 | sentence2 | |:--------|:----------------------------------------------------------------------------------|:------------------------------------------------------------------------------------| | type | string | string | | details | | | * Samples: | sentence1 | sentence2 | |:----------------------------------------------------------------|:----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------| | which gases are emitted from vehicles? | ['Particulate matter (PM). One type of particulate matter is the soot seen in vehicle exhaust. ... ', 'Volatile Organic Compounds (VOCs). ... ', 'Nitrogen oxides (NOx). ... ', 'Carbon monoxide (CO). ... ', 'Sulfur dioxide (SO2). ... ', 'Greenhouse gases.'] | | how long does it take for someone to not be drunk? | It takes 30 minutes to feel the effects of alcohol. Drinking more than one drink every 30 minutes means you are probably drinking too much, too fast. Slow yourself down, and if you find yourself feeling thirsty before those 30 minutes have passed, try a glass of water first. | | is ssdi taxable in ohio? | Social Security retirement benefits are fully exempt from state income taxes in Ohio. Any income from retirement accounts (like a 401(k) or an IRA) or pensions is taxed as regular income (but there are credits available). Social security benefits, if taxable on the federal return, are deducted on Ohio schedule A. | * Loss: [CachedGISTEmbedLoss](https://sbert.net/docs/package_reference/sentence_transformer/losses.html#cachedgistembedloss) with these parameters: ```json {'guide': SentenceTransformer( (0): Transformer({'max_seq_length': 512, 'do_lower_case': False}) with Transformer model: BertModel (1): Pooling({'word_embedding_dimension': 768, 'pooling_mode_cls_token': True, 'pooling_mode_mean_tokens': False, 'pooling_mode_max_tokens': False, 'pooling_mode_mean_sqrt_len_tokens': False, 'pooling_mode_weightedmean_tokens': False, 'pooling_mode_lasttoken': False, 'include_prompt': True}) (2): Normalize() ), 'temperature': 0.05} ``` #### paws-pos * Dataset: [paws-pos](https://huggingface.co/datasets/google-research-datasets/paws) at [161ece9](https://huggingface.co/datasets/google-research-datasets/paws/tree/161ece9501cf0a11f3e48bd356eaa82de46d6a09) * Size: 128 evaluation samples * Columns: sentence1 and sentence2 * Approximate statistics based on the first 1000 samples: | | sentence1 | sentence2 | |:--------|:-----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------| | type | string | string | | details | | | * Samples: | sentence1 | sentence2 | |:---------------------------------------------------------------------------------------------------------------------------------------------------------------|:---------------------------------------------------------------------------------------------------------------------------------------------------------------| | They were there to enjoy us and they were there to pray for us . | They were there for us to enjoy and they were there for us to pray . | | After the end of the war in June 1902 , Higgins left Southampton in the `` SSBavarian '' in August , returning to Cape Town the following month . | In August , after the end of the war in June 1902 , Higgins Southampton left the `` SSBavarian '' and returned to Cape Town the following month . | | From the merger of the Four Rivers Council and the Audubon Council , the Shawnee Trails Council was born . | Shawnee Trails Council was formed from the merger of the Four Rivers Council and the Audubon Council . | * Loss: [CachedGISTEmbedLoss](https://sbert.net/docs/package_reference/sentence_transformer/losses.html#cachedgistembedloss) with these parameters: ```json {'guide': SentenceTransformer( (0): Transformer({'max_seq_length': 512, 'do_lower_case': False}) with Transformer model: BertModel (1): Pooling({'word_embedding_dimension': 768, 'pooling_mode_cls_token': True, 'pooling_mode_mean_tokens': False, 'pooling_mode_max_tokens': False, 'pooling_mode_mean_sqrt_len_tokens': False, 'pooling_mode_weightedmean_tokens': False, 'pooling_mode_lasttoken': False, 'include_prompt': True}) (2): Normalize() ), 'temperature': 0.05} ``` ### Training Hyperparameters #### Non-Default Hyperparameters - `eval_strategy`: steps - `per_device_train_batch_size`: 640 - `per_device_eval_batch_size`: 64 - `learning_rate`: 3.5e-05 - `weight_decay`: 5e-05 - `num_train_epochs`: 2 - `lr_scheduler_type`: cosine_with_min_lr - `lr_scheduler_kwargs`: {'num_cycles': 0.5, 'min_lr': 6.999999999999999e-06} - `warmup_ratio`: 0.2 - `save_safetensors`: False - `fp16`: True - `push_to_hub`: True - `hub_model_id`: bobox/DeBERTa-small-ST-v1-test-step3-checkpoints-tmp - `hub_strategy`: all_checkpoints - `batch_sampler`: no_duplicates #### All Hyperparameters
Click to expand - `overwrite_output_dir`: False - `do_predict`: False - `eval_strategy`: steps - `prediction_loss_only`: True - `per_device_train_batch_size`: 640 - `per_device_eval_batch_size`: 64 - `per_gpu_train_batch_size`: None - `per_gpu_eval_batch_size`: None - `gradient_accumulation_steps`: 1 - `eval_accumulation_steps`: None - `torch_empty_cache_steps`: None - `learning_rate`: 3.5e-05 - `weight_decay`: 5e-05 - `adam_beta1`: 0.9 - `adam_beta2`: 0.999 - `adam_epsilon`: 1e-08 - `max_grad_norm`: 1.0 - `num_train_epochs`: 2 - `max_steps`: -1 - `lr_scheduler_type`: cosine_with_min_lr - `lr_scheduler_kwargs`: {'num_cycles': 0.5, 'min_lr': 6.999999999999999e-06} - `warmup_ratio`: 0.2 - `warmup_steps`: 0 - `log_level`: passive - `log_level_replica`: warning - `log_on_each_node`: True - `logging_nan_inf_filter`: True - `save_safetensors`: False - `save_on_each_node`: False - `save_only_model`: False - `restore_callback_states_from_checkpoint`: False - `no_cuda`: False - `use_cpu`: False - `use_mps_device`: False - `seed`: 42 - `data_seed`: None - `jit_mode_eval`: False - `use_ipex`: False - `bf16`: False - `fp16`: True - `fp16_opt_level`: O1 - `half_precision_backend`: auto - `bf16_full_eval`: False - `fp16_full_eval`: False - `tf32`: None - `local_rank`: 0 - `ddp_backend`: None - `tpu_num_cores`: None - `tpu_metrics_debug`: False - `debug`: [] - `dataloader_drop_last`: False - `dataloader_num_workers`: 0 - `dataloader_prefetch_factor`: None - `past_index`: -1 - `disable_tqdm`: False - `remove_unused_columns`: True - `label_names`: None - `load_best_model_at_end`: False - `ignore_data_skip`: False - `fsdp`: [] - `fsdp_min_num_params`: 0 - `fsdp_config`: {'min_num_params': 0, 'xla': False, 'xla_fsdp_v2': False, 'xla_fsdp_grad_ckpt': False} - `fsdp_transformer_layer_cls_to_wrap`: None - `accelerator_config`: {'split_batches': False, 'dispatch_batches': None, 'even_batches': True, 'use_seedable_sampler': True, 'non_blocking': False, 'gradient_accumulation_kwargs': None} - `deepspeed`: None - `label_smoothing_factor`: 0.0 - `optim`: adamw_torch - `optim_args`: None - `adafactor`: False - `group_by_length`: False - `length_column_name`: length - `ddp_find_unused_parameters`: None - `ddp_bucket_cap_mb`: None - `ddp_broadcast_buffers`: False - `dataloader_pin_memory`: True - `dataloader_persistent_workers`: False - `skip_memory_metrics`: True - `use_legacy_prediction_loop`: False - `push_to_hub`: True - `resume_from_checkpoint`: None - `hub_model_id`: bobox/DeBERTa-small-ST-v1-test-step3-checkpoints-tmp - `hub_strategy`: all_checkpoints - `hub_private_repo`: False - `hub_always_push`: False - `gradient_checkpointing`: False - `gradient_checkpointing_kwargs`: None - `include_inputs_for_metrics`: False - `eval_do_concat_batches`: True - `fp16_backend`: auto - `push_to_hub_model_id`: None - `push_to_hub_organization`: None - `mp_parameters`: - `auto_find_batch_size`: False - `full_determinism`: False - `torchdynamo`: None - `ray_scope`: last - `ddp_timeout`: 1800 - `torch_compile`: False - `torch_compile_backend`: None - `torch_compile_mode`: None - `dispatch_batches`: None - `split_batches`: None - `include_tokens_per_second`: False - `include_num_input_tokens_seen`: False - `neftune_noise_alpha`: None - `optim_target_modules`: None - `batch_eval_metrics`: False - `eval_on_start`: False - `eval_use_gather_object`: False - `batch_sampler`: no_duplicates - `multi_dataset_batch_sampler`: proportional
### Training Logs
Click to expand | Epoch | Step | Training Loss | paws-pos loss | trivia pairs loss | scitail-pairs-pos loss | scitail-pairs-qa loss | qasc pairs loss | sciq pairs loss | openbookqa pairs loss | msmarco pairs loss | nq pairs loss | vitaminc-pairs loss | xsum-pairs loss | gooaq pairs loss | negation-triplets loss | VitaminC_max_ap | sts-test_spearman_cosine | |:------:|:----:|:-------------:|:-------------:|:-----------------:|:----------------------:|:---------------------:|:---------------:|:---------------:|:---------------------:|:------------------:|:-------------:|:-------------------:|:---------------:|:----------------:|:----------------------:|:---------------:|:------------------------:| | 0.0022 | 1 | 0.8103 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.0045 | 2 | 0.8803 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.0067 | 3 | 0.8219 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.0090 | 4 | 0.0574 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.0112 | 5 | 0.3044 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.0135 | 6 | 0.3306 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.0157 | 7 | 0.759 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.0180 | 8 | 0.0472 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.0202 | 9 | 0.7782 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.0225 | 10 | 0.0757 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.0247 | 11 | 0.7778 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.0270 | 12 | 0.7111 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.0292 | 13 | 0.6598 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.0315 | 14 | 0.8901 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.0337 | 15 | 0.3206 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.0360 | 16 | 0.3408 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.0382 | 17 | 0.5623 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.0404 | 18 | 0.0758 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.0427 | 19 | 0.994 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.0449 | 20 | 2.4196 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.0472 | 21 | 0.0561 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.0494 | 22 | 0.0827 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.0517 | 23 | 0.7405 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.0539 | 24 | 0.9656 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.0562 | 25 | 0.7855 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.0584 | 26 | 0.6349 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.0607 | 27 | 0.8087 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.0629 | 28 | 0.9282 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.0652 | 29 | 0.3377 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.0674 | 30 | 0.3289 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.0697 | 31 | 0.6314 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.0719 | 32 | 0.0611 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.0742 | 33 | 0.8942 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.0764 | 34 | 0.0701 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.0787 | 35 | 0.8506 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.0809 | 36 | 0.3386 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.0831 | 37 | 0.0701 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.0854 | 38 | 0.8042 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.0876 | 39 | 0.8744 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.0899 | 40 | 0.8644 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.0921 | 41 | 0.8647 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.0944 | 42 | 0.7916 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.0966 | 43 | 0.8599 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.0989 | 44 | 0.0523 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.1011 | 45 | 0.6968 | 0.0245 | 0.5306 | 0.0737 | 0.0016 | 0.0908 | 0.0154 | 0.6755 | 0.1599 | 0.0959 | 1.7274 | 0.0382 | 0.2968 | 0.9175 | 0.5544 | 0.9038 | | 0.1034 | 46 | 0.3376 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.1056 | 47 | 0.5174 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.1079 | 48 | 0.8162 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.1101 | 49 | 0.3545 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.1124 | 50 | 0.315 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.1146 | 51 | 0.0627 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.1169 | 52 | 0.8851 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.1191 | 53 | 0.8382 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.1213 | 54 | 0.733 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.1236 | 55 | 0.7173 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.1258 | 56 | 0.7659 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.1281 | 57 | 0.793 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.1303 | 58 | 0.5426 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.1326 | 59 | 0.7641 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.1348 | 60 | 0.0657 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.1371 | 61 | 0.7836 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.1393 | 62 | 0.9306 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.1416 | 63 | 0.8673 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.1438 | 64 | 0.9296 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.1461 | 65 | 0.8211 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.1483 | 66 | 0.7685 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.1506 | 67 | 0.7139 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.1528 | 68 | 0.8241 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.1551 | 69 | 0.6256 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.1573 | 70 | 0.8842 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.1596 | 71 | 0.804 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.1618 | 72 | 0.0989 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.1640 | 73 | 0.332 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.1663 | 74 | 0.5736 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.1685 | 75 | 0.8285 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.1708 | 76 | 0.9561 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.1730 | 77 | 0.0633 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.1753 | 78 | 0.0848 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.1775 | 79 | 0.8325 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.1798 | 80 | 1.0011 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.1820 | 81 | 0.8697 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.1843 | 82 | 0.8344 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.1865 | 83 | 0.9967 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.1888 | 84 | 0.4638 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.1910 | 85 | 0.8994 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.1933 | 86 | 0.7789 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.1955 | 87 | 0.0555 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.1978 | 88 | 0.3778 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.2 | 89 | 0.708 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.2022 | 90 | 0.0689 | 0.0245 | 0.5192 | 0.0654 | 0.0016 | 0.0911 | 0.0158 | 0.7133 | 0.1517 | 0.0965 | 1.6142 | 0.0399 | 0.3071 | 0.9220 | 0.5542 | 0.9046 | | 0.2045 | 91 | 2.3489 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.2067 | 92 | 0.741 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.2090 | 93 | 0.7729 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.2112 | 94 | 0.0631 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.2135 | 95 | 0.9342 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.2157 | 96 | 0.8581 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.2180 | 97 | 0.5198 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.2202 | 98 | 0.846 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.2225 | 99 | 0.6581 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.2247 | 100 | 0.3579 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.2270 | 101 | 0.908 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.2292 | 102 | 0.0664 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.2315 | 103 | 0.5411 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.2337 | 104 | 0.9163 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.2360 | 105 | 0.7975 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.2382 | 106 | 0.37 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.2404 | 107 | 0.8495 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.2427 | 108 | 0.8073 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.2449 | 109 | 0.7563 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.2472 | 110 | 0.6585 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.2494 | 111 | 0.3246 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.2517 | 112 | 0.9718 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.2539 | 113 | 0.8584 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.2562 | 114 | 0.3385 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.2584 | 115 | 0.323 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.2607 | 116 | 0.3359 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.2629 | 117 | 0.6955 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.2652 | 118 | 0.0539 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.2674 | 119 | 0.0507 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.2697 | 120 | 0.314 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.2719 | 121 | 1.0339 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.2742 | 122 | 0.3158 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.2764 | 123 | 0.7809 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.2787 | 124 | 0.9516 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.2809 | 125 | 0.3117 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.2831 | 126 | 0.8366 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.2854 | 127 | 0.8033 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.2876 | 128 | 0.7253 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.2899 | 129 | 0.8345 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.2921 | 130 | 0.7532 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.2944 | 131 | 0.8247 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.2966 | 132 | 0.5175 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.2989 | 133 | 0.7813 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.3011 | 134 | 0.6582 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.3034 | 135 | 0.3484 | 0.0242 | 0.5458 | 0.0738 | 0.0015 | 0.0924 | 0.0162 | 0.6892 | 0.1677 | 0.0974 | 1.5520 | 0.0366 | 0.3082 | 0.9212 | 0.5518 | 0.9050 | | 0.3056 | 136 | 0.7648 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.3079 | 137 | 0.7554 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.3101 | 138 | 0.0753 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.3124 | 139 | 0.4987 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.3146 | 140 | 0.8543 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.3169 | 141 | 0.9425 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.3191 | 142 | 0.0472 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.3213 | 143 | 0.848 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.3236 | 144 | 0.8946 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.3258 | 145 | 0.7841 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.3281 | 146 | 0.6653 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.3303 | 147 | 0.3522 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.3326 | 148 | 0.4853 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.3348 | 149 | 0.4726 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.3371 | 150 | 0.8693 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.3393 | 151 | 0.8124 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.3416 | 152 | 0.8206 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.3438 | 153 | 0.9406 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.3461 | 154 | 0.7944 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.3483 | 155 | 0.0766 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.3506 | 156 | 0.8609 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.3528 | 157 | 1.0533 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.3551 | 158 | 0.8396 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.3573 | 159 | 0.7865 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.3596 | 160 | 2.4616 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.3618 | 161 | 0.0556 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.3640 | 162 | 0.3758 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.3663 | 163 | 0.9312 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.3685 | 164 | 0.7993 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.3708 | 165 | 0.8104 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.3730 | 166 | 0.8199 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.3753 | 167 | 1.0724 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.3775 | 168 | 0.3521 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.3798 | 169 | 0.8536 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.3820 | 170 | 0.872 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.3843 | 171 | 0.8009 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.3865 | 172 | 0.7798 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.3888 | 173 | 0.5953 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.3910 | 174 | 0.7562 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.3933 | 175 | 0.7227 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.3955 | 176 | 0.8953 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.3978 | 177 | 0.7102 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.4 | 178 | 0.0667 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.4022 | 179 | 0.0528 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.4045 | 180 | 0.7312 | 0.0241 | 0.5359 | 0.0916 | 0.0013 | 0.0949 | 0.0173 | 0.7253 | 0.1738 | 0.1032 | 1.5216 | 0.0496 | 0.3070 | 0.9813 | 0.5583 | 0.9055 | | 0.4067 | 181 | 0.7809 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.4090 | 182 | 0.8333 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.4112 | 183 | 0.9283 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.4135 | 184 | 0.7011 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.4157 | 185 | 0.8413 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.4180 | 186 | 1.1679 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.4202 | 187 | 0.8701 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.4225 | 188 | 0.8139 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.4247 | 189 | 0.664 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.4270 | 190 | 0.3835 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.4292 | 191 | 0.8516 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.4315 | 192 | 0.5479 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.4337 | 193 | 0.8642 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.4360 | 194 | 0.3121 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.4382 | 195 | 0.6932 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.4404 | 196 | 0.0647 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.4427 | 197 | 0.8173 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.4449 | 198 | 0.3122 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.4472 | 199 | 0.7852 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.4494 | 200 | 0.811 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.4517 | 201 | 0.7564 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.4539 | 202 | 0.0541 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.4562 | 203 | 0.9085 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.4584 | 204 | 0.8416 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.4607 | 205 | 0.0569 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.4629 | 206 | 0.7998 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.4652 | 207 | 0.7218 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.4674 | 208 | 0.9292 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.4697 | 209 | 0.8279 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.4719 | 210 | 0.8452 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.4742 | 211 | 1.1099 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.4764 | 212 | 0.9436 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.4787 | 213 | 0.8389 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.4809 | 214 | 0.3297 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.4831 | 215 | 0.8098 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.4854 | 216 | 0.0386 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.4876 | 217 | 0.7752 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.4899 | 218 | 0.8071 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.4921 | 219 | 2.571 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.4944 | 220 | 0.5912 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.4966 | 221 | 0.3792 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.4989 | 222 | 0.7456 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.5011 | 223 | 0.7207 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.5034 | 224 | 0.3254 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.5056 | 225 | 0.0461 | 0.0236 | 0.5324 | 0.0761 | 0.0012 | 0.0921 | 0.0165 | 0.7430 | 0.1787 | 0.0980 | 1.4897 | 0.0276 | 0.2668 | 0.9457 | 0.5573 | 0.9051 | | 0.5079 | 226 | 0.347 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.5101 | 227 | 0.0417 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.5124 | 228 | 0.7783 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.5146 | 229 | 0.9027 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.5169 | 230 | 0.7166 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.5191 | 231 | 0.705 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.5213 | 232 | 0.8425 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.5236 | 233 | 0.5362 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.5258 | 234 | 0.7869 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.5281 | 235 | 0.88 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.5303 | 236 | 0.8077 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.5326 | 237 | 0.8145 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.5348 | 238 | 0.78 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.5371 | 239 | 0.0536 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.5393 | 240 | 0.7975 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.5416 | 241 | 0.8932 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.5438 | 242 | 0.3386 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.5461 | 243 | 0.7741 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.5483 | 244 | 0.7439 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.5506 | 245 | 0.7999 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.5528 | 246 | 0.8542 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.5551 | 247 | 0.6992 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.5573 | 248 | 0.8579 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.5596 | 249 | 1.0221 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.5618 | 250 | 0.699 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.5640 | 251 | 0.8523 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.5663 | 252 | 1.0307 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.5685 | 253 | 0.846 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.5708 | 254 | 0.8361 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.5730 | 255 | 0.8224 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.5753 | 256 | 0.5301 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.5775 | 257 | 0.3795 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.5798 | 258 | 0.5434 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.5820 | 259 | 0.847 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.5843 | 260 | 0.7323 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.5865 | 261 | 0.6606 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.5888 | 262 | 0.0543 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.5910 | 263 | 0.6709 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.5933 | 264 | 0.809 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.5955 | 265 | 1.0391 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.5978 | 266 | 0.7396 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.6 | 267 | 0.7839 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.6022 | 268 | 0.3054 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.6045 | 269 | 0.5258 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.6067 | 270 | 0.7367 | 0.0244 | 0.4969 | 0.0964 | 0.0009 | 0.0913 | 0.0162 | 0.7336 | 0.1587 | 0.1078 | 1.4936 | 0.0269 | 0.3026 | 0.9505 | 0.5506 | 0.9085 | | 0.6090 | 271 | 0.747 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.6112 | 272 | 0.7855 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.6135 | 273 | 0.0473 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.6157 | 274 | 0.4378 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.6180 | 275 | 0.8767 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.6202 | 276 | 1.0345 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.6225 | 277 | 0.5182 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.6247 | 278 | 2.5949 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.6270 | 279 | 0.833 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.6292 | 280 | 0.0778 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.6315 | 281 | 0.8048 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.6337 | 282 | 0.7524 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.6360 | 283 | 0.3246 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.6382 | 284 | 0.0728 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.6404 | 285 | 2.3619 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.6427 | 286 | 0.7464 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.6449 | 287 | 0.6691 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.6472 | 288 | 0.059 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.6494 | 289 | 0.7841 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.6517 | 290 | 0.647 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.6539 | 291 | 0.8814 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.6562 | 292 | 0.7247 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.6584 | 293 | 0.059 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.6607 | 294 | 0.8317 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.6629 | 295 | 0.8548 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.6652 | 296 | 0.9213 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.6674 | 297 | 0.6923 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.6697 | 298 | 0.7777 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.6719 | 299 | 0.7496 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.6742 | 300 | 0.7636 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.6764 | 301 | 0.6867 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.6787 | 302 | 0.0506 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.6809 | 303 | 0.3346 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.6831 | 304 | 0.2485 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.6854 | 305 | 0.8508 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.6876 | 306 | 0.8464 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.6899 | 307 | 0.3385 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.6921 | 308 | 0.8837 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.6944 | 309 | 0.9019 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.6966 | 310 | 0.6922 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.6989 | 311 | 0.6348 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.7011 | 312 | 0.7522 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.7034 | 313 | 0.7843 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.7056 | 314 | 0.0493 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.7079 | 315 | 0.357 | 0.0240 | 0.5302 | 0.0995 | 0.0010 | 0.0917 | 0.0152 | 0.6922 | 0.1518 | 0.1014 | 1.4885 | 0.0278 | 0.2842 | 0.9598 | 0.5576 | 0.9068 | | 0.7101 | 316 | 0.841 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.7124 | 317 | 0.5849 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.7146 | 318 | 0.6818 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.7169 | 319 | 0.8269 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.7191 | 320 | 0.6979 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.7213 | 321 | 0.3218 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.7236 | 322 | 0.8206 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.7258 | 323 | 0.2106 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.7281 | 324 | 1.0524 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.7303 | 325 | 0.3774 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.7326 | 326 | 0.9098 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.7348 | 327 | 0.7988 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.7371 | 328 | 0.7916 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.7393 | 329 | 0.6314 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.7416 | 330 | 0.8628 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.7438 | 331 | 0.0688 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.7461 | 332 | 0.7386 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.7483 | 333 | 0.8458 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.7506 | 334 | 0.0442 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.7528 | 335 | 0.317 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.7551 | 336 | 0.8087 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.7573 | 337 | 0.3398 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.7596 | 338 | 0.699 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.7618 | 339 | 0.7901 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.7640 | 340 | 0.8072 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.7663 | 341 | 0.5939 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.7685 | 342 | 0.6933 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.7708 | 343 | 0.0437 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.7730 | 344 | 0.9882 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.7753 | 345 | 0.3707 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.7775 | 346 | 0.7103 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.7798 | 347 | 0.0372 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.7820 | 348 | 0.028 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.7843 | 349 | 0.7676 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.7865 | 350 | 0.6754 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.7888 | 351 | 0.0439 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.7910 | 352 | 0.8039 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.7933 | 353 | 0.0104 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.7955 | 354 | 0.0555 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.7978 | 355 | 0.8646 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.8 | 356 | 0.7781 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.8022 | 357 | 0.011 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.8045 | 358 | 0.3267 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.8067 | 359 | 2.5281 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.8090 | 360 | 0.301 | 0.0243 | 0.5313 | 0.1073 | 0.0006 | 0.1025 | 0.0160 | 0.6711 | 0.1452 | 0.1023 | 1.4291 | 0.0260 | 0.2771 | 0.9031 | 0.5599 | 0.9054 | | 0.8112 | 361 | 0.7533 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.8135 | 362 | 0.2958 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.8157 | 363 | 0.8296 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.8180 | 364 | 0.3191 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.8202 | 365 | 0.7866 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.8225 | 366 | 0.3157 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.8247 | 367 | 0.7402 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.8270 | 368 | 0.4957 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.8292 | 369 | 0.8505 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.8315 | 370 | 0.7702 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.8337 | 371 | 0.7591 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.8360 | 372 | 0.727 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.8382 | 373 | 0.3233 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.8404 | 374 | 0.8738 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.8427 | 375 | 0.0393 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.8449 | 376 | 0.7454 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.8472 | 377 | 0.8297 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.8494 | 378 | 0.7802 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.8517 | 379 | 0.6229 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.8539 | 380 | 0.0 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.8562 | 381 | 0.3506 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.8584 | 382 | 0.041 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.8607 | 383 | 0.725 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.8629 | 384 | 0.257 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.8652 | 385 | 0.7912 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.8674 | 386 | 0.8915 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.8697 | 387 | 0.779 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.8719 | 388 | 0.7828 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.8742 | 389 | 0.7462 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.8764 | 390 | 0.7913 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.8787 | 391 | 0.3209 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.8809 | 392 | 0.5932 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.8831 | 393 | 0.0613 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.8854 | 394 | 0.8802 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.8876 | 395 | 0.6116 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.8899 | 396 | 0.0537 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.8921 | 397 | 0.3006 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.8944 | 398 | 0.7636 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.8966 | 399 | 0.612 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.8989 | 400 | 0.54 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.9011 | 401 | 0.2761 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.9034 | 402 | 1.2668 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.9056 | 403 | 0.8066 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.9079 | 404 | 0.0094 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.9101 | 405 | 0.673 | 0.0242 | 0.4919 | 0.1050 | 0.0008 | 0.0942 | 0.0152 | 0.7152 | 0.1418 | 0.1087 | 1.4849 | 0.0285 | 0.2616 | 0.9024 | 0.5543 | 0.9052 | | 0.9124 | 406 | 0.5189 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.9146 | 407 | 0.649 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.9169 | 408 | 0.2982 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.9191 | 409 | 0.7511 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.9213 | 410 | 0.5164 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.9236 | 411 | 0.5924 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.9258 | 412 | 0.8191 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.9281 | 413 | 0.2311 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.9303 | 414 | 0.7421 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.9326 | 415 | 0.2936 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.9348 | 416 | 0.737 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.9371 | 417 | 0.6539 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.9393 | 418 | 0.6855 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.9416 | 419 | 0.8134 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.9438 | 420 | 0.6885 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.9461 | 421 | 0.5581 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.9483 | 422 | 0.8029 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.9506 | 423 | 0.8126 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.9528 | 424 | 0.8425 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.9551 | 425 | 0.049 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.9573 | 426 | 0.7849 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.9596 | 427 | 0.068 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.9618 | 428 | 0.2925 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.9640 | 429 | 0.777 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.9663 | 430 | 0.7397 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.9685 | 431 | 0.0007 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.9708 | 432 | 0.8535 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.9730 | 433 | 0.7026 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.9753 | 434 | 0.7557 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.9775 | 435 | 0.7225 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.9798 | 436 | 0.0 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.9820 | 437 | 0.4131 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.9843 | 438 | 0.2824 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.9865 | 439 | 0.3144 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.9888 | 440 | 0.0509 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.9910 | 441 | 0.7645 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.9933 | 442 | 0.2787 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.9955 | 443 | 0.64 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 0.9978 | 444 | 0.4045 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.0 | 445 | 0.7661 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.0022 | 446 | 0.7335 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.0045 | 447 | 0.7835 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.0067 | 448 | 0.7674 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.0090 | 449 | 0.0489 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.0112 | 450 | 0.3104 | 0.0251 | 0.4878 | 0.0699 | 0.0008 | 0.0959 | 0.0178 | 0.7217 | 0.1512 | 0.1032 | 1.4285 | 0.0287 | 0.2688 | 0.8765 | 0.5541 | 0.9043 | | 1.0135 | 451 | 0.2977 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.0157 | 452 | 0.7256 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.0180 | 453 | 0.0327 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.0202 | 454 | 0.7372 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.0225 | 455 | 0.0518 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.0247 | 456 | 0.7668 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.0270 | 457 | 0.6634 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.0292 | 458 | 0.6022 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.0315 | 459 | 0.7255 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.0337 | 460 | 0.2823 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.0360 | 461 | 0.2614 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.0382 | 462 | 0.5231 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.0404 | 463 | 0.0424 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.0427 | 464 | 0.9838 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.0449 | 465 | 2.4683 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.0472 | 466 | 0.0497 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.0494 | 467 | 0.0766 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.0517 | 468 | 0.7333 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.0539 | 469 | 0.7881 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.0562 | 470 | 0.7611 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.0584 | 471 | 0.6023 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.0607 | 472 | 0.7884 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.0629 | 473 | 0.8465 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.0652 | 474 | 0.2752 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.0674 | 475 | 0.2648 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.0697 | 476 | 0.5548 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.0719 | 477 | 0.0554 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.0742 | 478 | 0.8244 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.0764 | 479 | 0.0369 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.0787 | 480 | 0.747 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.0809 | 481 | 0.2507 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.0831 | 482 | 0.0304 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.0854 | 483 | 0.7735 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.0876 | 484 | 0.7526 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.0899 | 485 | 0.7959 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.0921 | 486 | 0.7405 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.0944 | 487 | 0.7041 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.0966 | 488 | 0.6991 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.0989 | 489 | 0.0462 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.1011 | 490 | 0.5835 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.1034 | 491 | 0.2632 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.1056 | 492 | 0.4681 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.1079 | 493 | 0.7271 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.1101 | 494 | 0.2582 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.1124 | 495 | 0.2251 | 0.0239 | 0.5306 | 0.0761 | 0.0005 | 0.1029 | 0.0153 | 0.6792 | 0.1548 | 0.0933 | 1.3855 | 0.0206 | 0.2823 | 0.8651 | 0.5517 | 0.9052 | | 1.1146 | 496 | 0.0385 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.1169 | 497 | 0.7277 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.1191 | 498 | 0.705 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.1213 | 499 | 0.6059 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.1236 | 500 | 0.6156 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.1258 | 501 | 0.6809 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.1281 | 502 | 0.7104 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.1303 | 503 | 0.4397 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.1326 | 504 | 0.6952 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.1348 | 505 | 0.0557 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.1371 | 506 | 0.6711 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.1393 | 507 | 0.7173 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.1416 | 508 | 0.7037 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.1438 | 509 | 0.8578 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.1461 | 510 | 0.6712 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.1483 | 511 | 0.7472 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.1506 | 512 | 0.5911 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.1528 | 513 | 0.6827 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.1551 | 514 | 0.5034 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.1573 | 515 | 0.8367 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.1596 | 516 | 0.6596 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.1618 | 517 | 0.0859 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.1640 | 518 | 0.2797 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.1663 | 519 | 0.5181 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.1685 | 520 | 0.6837 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.1708 | 521 | 0.7238 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.1730 | 522 | 0.0318 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.1753 | 523 | 0.0694 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.1775 | 524 | 0.7472 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.1798 | 525 | 0.8912 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.1820 | 526 | 0.7744 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.1843 | 527 | 0.6869 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.1865 | 528 | 0.8497 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.1888 | 529 | 0.4281 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.1910 | 530 | 0.7605 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.1933 | 531 | 0.6354 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.1955 | 532 | 0.0518 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.1978 | 533 | 0.2602 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.2 | 534 | 0.5082 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.2022 | 535 | 0.0603 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.2045 | 536 | 2.3371 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.2067 | 537 | 0.6513 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.2090 | 538 | 0.6053 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.2112 | 539 | 0.0544 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.2135 | 540 | 0.7219 | 0.0242 | 0.5325 | 0.0872 | 0.0007 | 0.0975 | 0.0165 | 0.6885 | 0.1340 | 0.0944 | 1.3777 | 0.0253 | 0.2804 | 0.8755 | 0.5533 | 0.9066 | | 1.2157 | 541 | 0.6862 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.2180 | 542 | 0.4639 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.2202 | 543 | 0.6663 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.2225 | 544 | 0.5047 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.2247 | 545 | 0.2306 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.2270 | 546 | 0.7147 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.2292 | 547 | 0.0344 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.2315 | 548 | 0.4429 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.2337 | 549 | 0.6966 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.2360 | 550 | 0.6926 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.2382 | 551 | 0.261 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.2404 | 552 | 0.6558 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.2427 | 553 | 0.6285 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.2449 | 554 | 0.6471 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.2472 | 555 | 0.4989 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.2494 | 556 | 0.195 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.2517 | 557 | 0.8431 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.2539 | 558 | 0.642 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.2562 | 559 | 0.2251 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.2584 | 560 | 0.2057 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.2607 | 561 | 0.2198 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.2629 | 562 | 0.4856 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.2652 | 563 | 0.0273 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.2674 | 564 | 0.0302 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.2697 | 565 | 0.1863 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.2719 | 566 | 0.8053 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.2742 | 567 | 0.1935 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.2764 | 568 | 0.5837 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.2787 | 569 | 0.7606 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.2809 | 570 | 0.1904 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.2831 | 571 | 0.6585 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.2854 | 572 | 0.7043 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.2876 | 573 | 0.6083 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.2899 | 574 | 0.6523 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.2921 | 575 | 0.553 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.2944 | 576 | 0.6234 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.2966 | 577 | 0.4428 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.2989 | 578 | 0.5433 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.3011 | 579 | 0.4937 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.3034 | 580 | 0.2222 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.3056 | 581 | 0.5672 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.3079 | 582 | 0.6562 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.3101 | 583 | 0.056 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.3124 | 584 | 0.4015 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.3146 | 585 | 0.6675 | 0.0242 | 0.4988 | 0.0997 | 0.0007 | 0.0983 | 0.0161 | 0.7107 | 0.1444 | 0.0869 | 1.3895 | 0.0208 | 0.2780 | 0.9073 | 0.5507 | 0.9080 | | 1.3169 | 586 | 0.7298 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.3191 | 587 | 0.0372 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.3213 | 588 | 0.7247 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.3236 | 589 | 0.6839 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.3258 | 590 | 0.6848 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.3281 | 591 | 0.4449 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.3303 | 592 | 0.2104 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.3326 | 593 | 0.391 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.3348 | 594 | 0.3641 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.3371 | 595 | 0.6953 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.3393 | 596 | 0.6382 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.3416 | 597 | 0.6245 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.3438 | 598 | 0.6775 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.3461 | 599 | 0.5727 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.3483 | 600 | 0.0567 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.3506 | 601 | 0.6258 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.3528 | 602 | 0.8138 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.3551 | 603 | 0.6099 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.3573 | 604 | 0.6801 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.3596 | 605 | 2.2003 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.3618 | 606 | 0.052 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.3640 | 607 | 0.2175 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.3663 | 608 | 0.7671 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.3685 | 609 | 0.5524 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.3708 | 610 | 0.5868 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.3730 | 611 | 0.6628 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.3753 | 612 | 0.8106 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.3775 | 613 | 0.2 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.3798 | 614 | 0.57 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.3820 | 615 | 0.6329 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.3843 | 616 | 0.5616 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.3865 | 617 | 0.6678 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.3888 | 618 | 0.454 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.3910 | 619 | 0.5198 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.3933 | 620 | 0.5259 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.3955 | 621 | 0.714 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.3978 | 622 | 0.4943 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.4 | 623 | 0.0324 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.4022 | 624 | 0.0305 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.4045 | 625 | 0.5194 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.4067 | 626 | 0.5412 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.4090 | 627 | 0.5688 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.4112 | 628 | 0.7636 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.4135 | 629 | 0.478 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.4157 | 630 | 0.5674 | 0.0240 | 0.4915 | 0.1026 | 0.0006 | 0.0886 | 0.0171 | 0.7429 | 0.1468 | 0.0846 | 1.4192 | 0.0243 | 0.2606 | 0.9350 | 0.5566 | 0.9058 | | 1.4180 | 631 | 0.9232 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.4202 | 632 | 0.613 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.4225 | 633 | 0.5689 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.4247 | 634 | 0.4126 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.4270 | 635 | 0.2148 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.4292 | 636 | 0.7029 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.4315 | 637 | 0.3989 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.4337 | 638 | 0.6291 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.4360 | 639 | 0.158 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.4382 | 640 | 0.4833 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.4404 | 641 | 0.0561 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.4427 | 642 | 0.6613 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.4449 | 643 | 0.1917 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.4472 | 644 | 0.5755 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.4494 | 645 | 0.5609 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.4517 | 646 | 0.5407 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.4539 | 647 | 0.0455 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.4562 | 648 | 0.6599 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.4584 | 649 | 0.6952 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.4607 | 650 | 0.0329 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.4629 | 651 | 0.6939 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.4652 | 652 | 0.4664 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.4674 | 653 | 0.6686 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.4697 | 654 | 0.6167 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.4719 | 655 | 0.6612 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.4742 | 656 | 0.8139 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.4764 | 657 | 0.6813 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.4787 | 658 | 0.6031 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.4809 | 659 | 0.1783 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.4831 | 660 | 0.6536 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.4854 | 661 | 0.0318 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.4876 | 662 | 0.6372 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.4899 | 663 | 0.5695 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.4921 | 664 | 2.3259 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.4944 | 665 | 0.4342 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.4966 | 666 | 0.2176 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.4989 | 667 | 0.5419 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.5011 | 668 | 0.4976 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.5034 | 669 | 0.1964 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.5056 | 670 | 0.0311 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.5079 | 671 | 0.1832 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.5101 | 672 | 0.0345 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.5124 | 673 | 0.5376 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.5146 | 674 | 0.6316 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.5169 | 675 | 0.5025 | 0.0239 | 0.5190 | 0.0944 | 0.0006 | 0.0907 | 0.0164 | 0.7405 | 0.1450 | 0.0895 | 1.3485 | 0.0209 | 0.2531 | 0.9070 | 0.5589 | 0.9067 | | 1.5191 | 676 | 0.509 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.5213 | 677 | 0.6078 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.5236 | 678 | 0.3961 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.5258 | 679 | 0.5699 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.5281 | 680 | 0.6305 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.5303 | 681 | 0.5886 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.5326 | 682 | 0.6432 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.5348 | 683 | 0.614 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.5371 | 684 | 0.0432 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.5393 | 685 | 0.633 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.5416 | 686 | 0.6228 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.5438 | 687 | 0.2105 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.5461 | 688 | 0.5429 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.5483 | 689 | 0.5361 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.5506 | 690 | 0.5567 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.5528 | 691 | 0.6131 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.5551 | 692 | 0.5111 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.5573 | 693 | 0.6216 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.5596 | 694 | 0.7615 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.5618 | 695 | 0.51 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.5640 | 696 | 0.6989 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.5663 | 697 | 0.8145 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.5685 | 698 | 0.5928 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.5708 | 699 | 0.6046 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.5730 | 700 | 0.6483 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.5753 | 701 | 0.3976 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.5775 | 702 | 0.2033 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.5798 | 703 | 0.4127 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.5820 | 704 | 0.6008 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.5843 | 705 | 0.5346 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.5865 | 706 | 0.4183 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.5888 | 707 | 0.0245 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.5910 | 708 | 0.4834 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.5933 | 709 | 0.5815 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.5955 | 710 | 0.7791 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.5978 | 711 | 0.4835 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.6 | 712 | 0.5797 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.6022 | 713 | 0.1891 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.6045 | 714 | 0.3955 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.6067 | 715 | 0.497 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.6090 | 716 | 0.6271 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.6112 | 717 | 0.5571 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.6135 | 718 | 0.0405 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.6157 | 719 | 0.2968 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.6180 | 720 | 0.7262 | 0.0241 | 0.4987 | 0.1010 | 0.0007 | 0.0932 | 0.0165 | 0.7172 | 0.1424 | 0.0960 | 1.3777 | 0.0198 | 0.2702 | 0.9084 | 0.5552 | 0.9091 | | 1.6202 | 721 | 0.7611 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.6225 | 722 | 0.3926 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.6247 | 723 | 2.3127 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.6270 | 724 | 0.7026 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.6292 | 725 | 0.0685 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.6315 | 726 | 0.6031 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.6337 | 727 | 0.579 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.6360 | 728 | 0.1705 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.6382 | 729 | 0.0591 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.6404 | 730 | 2.1115 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.6427 | 731 | 0.4871 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.6449 | 732 | 0.4263 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.6472 | 733 | 0.0484 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.6494 | 734 | 0.5249 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.6517 | 735 | 0.3998 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.6539 | 736 | 0.7226 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.6562 | 737 | 0.4494 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.6584 | 738 | 0.0537 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.6607 | 739 | 0.7129 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.6629 | 740 | 0.6079 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.6652 | 741 | 0.6688 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.6674 | 742 | 0.567 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.6697 | 743 | 0.5196 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.6719 | 744 | 0.5081 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.6742 | 745 | 0.5413 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.6764 | 746 | 0.4741 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.6787 | 747 | 0.0289 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.6809 | 748 | 0.1956 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.6831 | 749 | 0.1967 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.6854 | 750 | 0.6488 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.6876 | 751 | 0.7052 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.6899 | 752 | 0.1807 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.6921 | 753 | 0.6238 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.6944 | 754 | 0.6328 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.6966 | 755 | 0.4677 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.6989 | 756 | 0.44 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.7011 | 757 | 0.5382 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.7034 | 758 | 0.6094 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.7056 | 759 | 0.0262 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.7079 | 760 | 0.1995 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.7101 | 761 | 0.6595 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.7124 | 762 | 0.4056 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.7146 | 763 | 0.4836 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.7169 | 764 | 0.5474 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.7191 | 765 | 0.6019 | 0.0240 | 0.5037 | 0.1004 | 0.0006 | 0.0951 | 0.0160 | 0.7151 | 0.1363 | 0.0948 | 1.4008 | 0.0213 | 0.2534 | 0.9053 | 0.5581 | 0.9094 | | 1.7213 | 766 | 0.1824 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.7236 | 767 | 0.6398 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.7258 | 768 | 0.1518 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.7281 | 769 | 0.7804 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.7303 | 770 | 0.2294 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.7326 | 771 | 0.719 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.7348 | 772 | 0.61 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.7371 | 773 | 0.5865 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.7393 | 774 | 0.4411 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.7416 | 775 | 0.6174 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.7438 | 776 | 0.0526 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.7461 | 777 | 0.5093 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.7483 | 778 | 0.6742 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.7506 | 779 | 0.0293 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.7528 | 780 | 0.1776 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.7551 | 781 | 0.6964 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.7573 | 782 | 0.2044 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.7596 | 783 | 0.5221 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.7618 | 784 | 0.579 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.7640 | 785 | 0.5887 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.7663 | 786 | 0.4357 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.7685 | 787 | 0.5437 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.7708 | 788 | 0.0326 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.7730 | 789 | 0.7279 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.7753 | 790 | 0.2255 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.7775 | 791 | 0.5386 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.7798 | 792 | 0.0218 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.7820 | 793 | 0.0174 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.7843 | 794 | 0.542 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.7865 | 795 | 0.511 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.7888 | 796 | 0.0345 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.7910 | 797 | 0.6513 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.7933 | 798 | 0.0069 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.7955 | 799 | 0.0467 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.7978 | 800 | 0.6994 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.8 | 801 | 0.6583 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.8022 | 802 | 0.0059 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.8045 | 803 | 0.1896 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.8067 | 804 | 2.2539 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.8090 | 805 | 0.1933 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.8112 | 806 | 0.5681 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.8135 | 807 | 0.1692 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.8157 | 808 | 0.6595 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.8180 | 809 | 0.1603 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.8202 | 810 | 0.6671 | 0.0245 | 0.4944 | 0.1077 | 0.0005 | 0.0981 | 0.0158 | 0.6886 | 0.1277 | 0.0865 | 1.3900 | 0.0200 | 0.2530 | 0.8990 | 0.5586 | 0.9083 | | 1.8225 | 811 | 0.1995 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.8247 | 812 | 0.5579 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.8270 | 813 | 0.3833 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.8292 | 814 | 0.6411 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.8315 | 815 | 0.6034 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.8337 | 816 | 0.5206 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.8360 | 817 | 0.5941 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.8382 | 818 | 0.2062 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.8404 | 819 | 0.6086 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.8427 | 820 | 0.037 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.8449 | 821 | 0.6257 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.8472 | 822 | 0.7064 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.8494 | 823 | 0.563 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.8517 | 824 | 0.4359 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.8539 | 825 | 0.0 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.8562 | 826 | 0.233 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.8584 | 827 | 0.0335 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.8607 | 828 | 0.6077 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.8629 | 829 | 0.1707 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.8652 | 830 | 0.5807 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.8674 | 831 | 0.6566 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.8697 | 832 | 0.663 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.8719 | 833 | 0.5896 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.8742 | 834 | 0.5418 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.8764 | 835 | 0.5735 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.8787 | 836 | 0.2062 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.8809 | 837 | 0.4343 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.8831 | 838 | 0.0614 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.8854 | 839 | 0.6301 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.8876 | 840 | 0.3956 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.8899 | 841 | 0.0479 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.8921 | 842 | 0.1819 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.8944 | 843 | 0.6005 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.8966 | 844 | 0.452 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.8989 | 845 | 0.4083 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.9011 | 846 | 0.1702 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.9034 | 847 | 0.9503 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.9056 | 848 | 0.6427 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.9079 | 849 | 0.0048 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.9101 | 850 | 0.4609 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.9124 | 851 | 0.3854 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.9146 | 852 | 0.4411 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.9169 | 853 | 0.181 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.9191 | 854 | 0.5846 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.9213 | 855 | 0.3585 | 0.0243 | 0.4916 | 0.1050 | 0.0006 | 0.0897 | 0.0162 | 0.6815 | 0.1330 | 0.0923 | 1.3997 | 0.0198 | 0.2540 | 0.8800 | 0.5565 | 0.9085 | | 1.9236 | 856 | 0.4303 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.9258 | 857 | 0.5627 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.9281 | 858 | 0.1687 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.9303 | 859 | 0.5509 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.9326 | 860 | 0.175 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.9348 | 861 | 0.605 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.9371 | 862 | 0.5085 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.9393 | 863 | 0.5059 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.9416 | 864 | 0.6114 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.9438 | 865 | 0.5132 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.9461 | 866 | 0.4178 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.9483 | 867 | 0.6022 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.9506 | 868 | 0.5691 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.9528 | 869 | 0.7299 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.9551 | 870 | 0.0441 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.9573 | 871 | 0.5855 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.9596 | 872 | 0.0151 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.9618 | 873 | 0.184 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.9640 | 874 | 0.6185 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.9663 | 875 | 0.6474 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.9685 | 876 | 0.0005 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.9708 | 877 | 0.6692 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.9730 | 878 | 0.496 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.9753 | 879 | 0.5654 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.9775 | 880 | 0.4925 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.9798 | 881 | 0.0 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.9820 | 882 | 0.2304 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.9843 | 883 | 0.1772 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.9865 | 884 | 0.1804 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.9888 | 885 | 0.0198 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.9910 | 886 | 0.6703 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.9933 | 887 | 0.1552 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.9955 | 888 | 0.4962 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 1.9978 | 889 | 0.2099 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | | 2.0 | 890 | 0.6554 | 0.0246 | 0.4886 | 0.0966 | 0.0005 | 0.0885 | 0.0164 | 0.6816 | 0.1300 | 0.0919 | 1.3958 | 0.0203 | 0.2583 | 0.8738 | 0.5563 | 0.9077 |
### Framework Versions - Python: 3.10.14 - Sentence Transformers: 3.0.1 - Transformers: 4.44.0 - PyTorch: 2.4.0 - Accelerate: 0.33.0 - Datasets: 2.21.0 - Tokenizers: 0.19.1 ## Citation ### BibTeX #### Sentence Transformers ```bibtex @inproceedings{reimers-2019-sentence-bert, title = "Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks", author = "Reimers, Nils and Gurevych, Iryna", booktitle = "Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing", month = "11", year = "2019", publisher = "Association for Computational Linguistics", url = "https://arxiv.org/abs/1908.10084", } ```