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Training in progress, step 2355, checkpoint
54b6ec3 verified
metadata
base_model: microsoft/deberta-v2-xlarge
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:99622
  - loss:CachedGISTEmbedLoss
widget:
  - source_sentence: does alcohol cause anxiety
    sentences:
      - "Kim Jong Unâ\x80\x99s Wife â\x80\x98Missingâ\x80\x99, Assumed Pregnant. Kim Jong Unâ\x80\x99s wife, Ri Sol Ju, has reportedly â\x80\x98gone missingâ\x80\x99 after not making any public appearances for the last 40 days, according to data released by North Korea news-monitoring website NK News."
      - "Japan is the worldâ\x80\x99s largest mobile games market, with $6.2 billion in 2015E revenue. Despite having fewer players than China or the U.S., Japan has the highest average mobile games spending of any major country. China has 785 million mobile gamers, 62% of Asiaâ\x80\x99s total."
      - >-
        Alcohol Causes Anxiety and Behavior Changes. Frequent alcohol
        consumption can extremely impair several functions of your brain
        including the area that is responsible for controlling your behavior.
        This is why as you consume alcohol, your behavior, conduct and other
        cognitive abilities will usually be the first to go.
  - source_sentence: >-
      More than 273 people have died from the 2019-20 coronavirus outside
      mainland China .
    sentences:
      - >-
        More than 3,700 people have died : around 3,100 in mainland China and
        around 550 in all other countries combined .
      - >-
        More than 3,200 people have died : almost 3,000 in mainland China and
        around 275 in other countries .
      - more than 4,900 deaths have been attributed to COVID-19 .
  - source_sentence: >-
      The action of flushing the toilet, performed multiple times daily, is the
      single biggest use of water in the home.
    sentences:
      - >-
        What action, performed multiple times daily, is the single biggest use
        of water in the home?
      - >-
        Which of these would most likely improve the air quality in large Texas
        cities?
      - The innermost layer of the sun is known as what?
  - source_sentence: >-
      You call cellular respiration that does not need oxygen to proceed
      anaerobic respiration.
    sentences:
      - A binary molecular compound is made up of two of what?
      - >-
        What do you call cellular respiration that does not need oxygen to
        proceed?
      - Roots grow in length and width from the primary and secondary what?
  - source_sentence: >-
      What was the cause of the disqualification of Swedish pentathlete
      Hans-Gunnar Liljenwall at Mexico City in 1968, the first as a result of
      failing a doping test at an Olympic Games?
    sentences:
      - >-
        'Cogito, ergo sum' - the meaning and origin of this phrase Cogito, ergo
        sum Usually translated from the Latin as 'I think, therefore I am'.
        Origin Possibly the best known of all philosophical quotations; this is
        from the French philosopher René Descartes in Discourse on Method, 1637,
        where he attempted to prove his existence as a thinking being, by
        thinking. 'I think, therefore I am' comes to us in English via two
        translations. Descartes' original statement in French was "Je pense,
        donc je suis". This is such a well-known line that it has spawned
        humorous alternatives, not least: "I'm pink, therefore I'm spam" "René
        Descartes was a drunken fart - I drink therefore I am".
      - "Hans Gunnar Liljenwall - Alchetron, The Free Social Encyclopedia I Love to read n write about Interesting People Hans Gunnar Liljenwall Role\_\_Olympic athlete Born\_\_9 July 1941 (age\_74) (1941-07-09) Hans-Gunnar Liljenwall (born 9 July 1941) is a Swedish modern pentathlete who caused the disqualification of the Swedish men's team at the 1968 Summer Olympics held in Mexico City for his alcohol use. Liljenwall was the first athlete to be disqualified at the Olympics for drug use, following the introduction of anti-doping regulations by the International Olympic Committee in 1967. Sponsored Links Liljenwall reportedly had \"two beers\" to calm his nerves before the pistol shooting portion of the modern pentathlon. The Swedish team eventually had to return their bronze medals."
      - >-
        Erstwhile | Definition of Erstwhile by Merriam-Webster Examples of
        erstwhile in a sentence <there's now a store where erstwhile lay green
        and pleasant pastures> Did You Know? The adverb erstwhile has been part
        of English since the 16th century, but it is formed from two words that
        are much older. It comes from the Old English words ær, meaning "early,"
        and hwīl, which has much the same meaning as the modern word while. (The
        English word ere, meaning "before," is also descendant of ær.) The
        adjective erstwhile, as in erstwhile enemies, joined the language around
        1900. 1569 First Known Use of erstwhile 1569
model-index:
  - name: SentenceTransformer based on microsoft/deberta-v2-xlarge
    results:
      - task:
          type: semantic-similarity
          name: Semantic Similarity
        dataset:
          name: sts test
          type: sts-test
        metrics:
          - type: pearson_cosine
            value: 0.9160506859420039
            name: Pearson Cosine
          - type: spearman_cosine
            value: 0.9257037838059433
            name: Spearman Cosine
          - type: pearson_manhattan
            value: 0.9279650883873299
            name: Pearson Manhattan
          - type: spearman_manhattan
            value: 0.9244578639375454
            name: Spearman Manhattan
          - type: pearson_euclidean
            value: 0.9289059375496083
            name: Pearson Euclidean
          - type: spearman_euclidean
            value: 0.9252091928650454
            name: Spearman Euclidean
          - type: pearson_dot
            value: 0.9064020147620191
            name: Pearson Dot
          - type: spearman_dot
            value: 0.9074262946234223
            name: Spearman Dot
          - type: pearson_max
            value: 0.9289059375496083
            name: Pearson Max
          - type: spearman_max
            value: 0.9257037838059433
            name: Spearman Max
      - task:
          type: binary-classification
          name: Binary Classification
        dataset:
          name: allNLI dev
          type: allNLI-dev
        metrics:
          - type: cosine_accuracy
            value: 0.71484375
            name: Cosine Accuracy
          - type: cosine_accuracy_threshold
            value: 0.8047086000442505
            name: Cosine Accuracy Threshold
          - type: cosine_f1
            value: 0.6310679611650486
            name: Cosine F1
          - type: cosine_f1_threshold
            value: 0.659548282623291
            name: Cosine F1 Threshold
          - type: cosine_precision
            value: 0.5439330543933054
            name: Cosine Precision
          - type: cosine_recall
            value: 0.7514450867052023
            name: Cosine Recall
          - type: cosine_ap
            value: 0.6080113352779702
            name: Cosine Ap
          - type: dot_accuracy
            value: 0.72265625
            name: Dot Accuracy
          - type: dot_accuracy_threshold
            value: 816.7735595703125
            name: Dot Accuracy Threshold
          - type: dot_f1
            value: 0.620985010706638
            name: Dot F1
          - type: dot_f1_threshold
            value: 640.6546020507812
            name: Dot F1 Threshold
          - type: dot_precision
            value: 0.4931972789115646
            name: Dot Precision
          - type: dot_recall
            value: 0.838150289017341
            name: Dot Recall
          - type: dot_ap
            value: 0.600457833078373
            name: Dot Ap
          - type: manhattan_accuracy
            value: 0.71875
            name: Manhattan Accuracy
          - type: manhattan_accuracy_threshold
            value: 758.1986083984375
            name: Manhattan Accuracy Threshold
          - type: manhattan_f1
            value: 0.6270783847980997
            name: Manhattan F1
          - type: manhattan_f1_threshold
            value: 839.986572265625
            name: Manhattan F1 Threshold
          - type: manhattan_precision
            value: 0.532258064516129
            name: Manhattan Precision
          - type: manhattan_recall
            value: 0.7630057803468208
            name: Manhattan Recall
          - type: manhattan_ap
            value: 0.6045263522674633
            name: Manhattan Ap
          - type: euclidean_accuracy
            value: 0.720703125
            name: Euclidean Accuracy
          - type: euclidean_accuracy_threshold
            value: 24.504844665527344
            name: Euclidean Accuracy Threshold
          - type: euclidean_f1
            value: 0.6252983293556086
            name: Euclidean F1
          - type: euclidean_f1_threshold
            value: 26.812313079833984
            name: Euclidean F1 Threshold
          - type: euclidean_precision
            value: 0.532520325203252
            name: Euclidean Precision
          - type: euclidean_recall
            value: 0.7572254335260116
            name: Euclidean Recall
          - type: euclidean_ap
            value: 0.6046133720555715
            name: Euclidean Ap
          - type: max_accuracy
            value: 0.72265625
            name: Max Accuracy
          - type: max_accuracy_threshold
            value: 816.7735595703125
            name: Max Accuracy Threshold
          - type: max_f1
            value: 0.6310679611650486
            name: Max F1
          - type: max_f1_threshold
            value: 839.986572265625
            name: Max F1 Threshold
          - type: max_precision
            value: 0.5439330543933054
            name: Max Precision
          - type: max_recall
            value: 0.838150289017341
            name: Max Recall
          - type: max_ap
            value: 0.6080113352779702
            name: Max Ap
      - task:
          type: binary-classification
          name: Binary Classification
        dataset:
          name: Qnli dev
          type: Qnli-dev
        metrics:
          - type: cosine_accuracy
            value: 0.681640625
            name: Cosine Accuracy
          - type: cosine_accuracy_threshold
            value: 0.7123683094978333
            name: Cosine Accuracy Threshold
          - type: cosine_f1
            value: 0.7010309278350516
            name: Cosine F1
          - type: cosine_f1_threshold
            value: 0.5615949630737305
            name: Cosine F1 Threshold
          - type: cosine_precision
            value: 0.5895953757225434
            name: Cosine Precision
          - type: cosine_recall
            value: 0.864406779661017
            name: Cosine Recall
          - type: cosine_ap
            value: 0.7201932202052597
            name: Cosine Ap
          - type: dot_accuracy
            value: 0.673828125
            name: Dot Accuracy
          - type: dot_accuracy_threshold
            value: 685.181884765625
            name: Dot Accuracy Threshold
          - type: dot_f1
            value: 0.6969205834683955
            name: Dot F1
          - type: dot_f1_threshold
            value: 513.651123046875
            name: Dot F1 Threshold
          - type: dot_precision
            value: 0.5643044619422573
            name: Dot Precision
          - type: dot_recall
            value: 0.9110169491525424
            name: Dot Recall
          - type: dot_ap
            value: 0.6897146478507191
            name: Dot Ap
          - type: manhattan_accuracy
            value: 0.681640625
            name: Manhattan Accuracy
          - type: manhattan_accuracy_threshold
            value: 807.0958251953125
            name: Manhattan Accuracy Threshold
          - type: manhattan_f1
            value: 0.6993243243243245
            name: Manhattan F1
          - type: manhattan_f1_threshold
            value: 923.9697265625
            name: Manhattan F1 Threshold
          - type: manhattan_precision
            value: 0.5814606741573034
            name: Manhattan Precision
          - type: manhattan_recall
            value: 0.8771186440677966
            name: Manhattan Recall
          - type: manhattan_ap
            value: 0.7263357505187384
            name: Manhattan Ap
          - type: euclidean_accuracy
            value: 0.685546875
            name: Euclidean Accuracy
          - type: euclidean_accuracy_threshold
            value: 25.745054244995117
            name: Euclidean Accuracy Threshold
          - type: euclidean_f1
            value: 0.6986754966887417
            name: Euclidean F1
          - type: euclidean_f1_threshold
            value: 30.013221740722656
            name: Euclidean F1 Threshold
          - type: euclidean_precision
            value: 0.5733695652173914
            name: Euclidean Precision
          - type: euclidean_recall
            value: 0.8940677966101694
            name: Euclidean Recall
          - type: euclidean_ap
            value: 0.7272320129102358
            name: Euclidean Ap
          - type: max_accuracy
            value: 0.685546875
            name: Max Accuracy
          - type: max_accuracy_threshold
            value: 807.0958251953125
            name: Max Accuracy Threshold
          - type: max_f1
            value: 0.7010309278350516
            name: Max F1
          - type: max_f1_threshold
            value: 923.9697265625
            name: Max F1 Threshold
          - type: max_precision
            value: 0.5895953757225434
            name: Max Precision
          - type: max_recall
            value: 0.9110169491525424
            name: Max Recall
          - type: max_ap
            value: 0.7272320129102358
            name: Max Ap

SentenceTransformer based on microsoft/deberta-v2-xlarge

This is a sentence-transformers model finetuned from microsoft/deberta-v2-xlarge on the negation-triplets, vitaminc-pairs, scitail-pairs-qa, scitail-pairs-pos, xsum-pairs, sciq_pairs, qasc_pairs, openbookqa_pairs, msmarco_pairs, nq_pairs, trivia_pairs, gooaq_pairs, paws-pos and global_dataset datasets. It maps sentences & paragraphs to a 1536-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 Sources

Full Model Architecture

SentenceTransformer(
  (0): Transformer({'max_seq_length': 512, 'do_lower_case': False}) with Transformer model: DebertaV2Model 
  (1): Pooling({'word_embedding_dimension': 1536, '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:

pip install -U sentence-transformers

Then you can load this model and run inference.

from sentence_transformers import SentenceTransformer

# Download from the 🤗 Hub
model = SentenceTransformer("bobox/DeBERTa2-0.9B-ST-v1-checkpoints-tmp")
# Run inference
sentences = [
    'What was the cause of the disqualification of Swedish pentathlete Hans-Gunnar Liljenwall at Mexico City in 1968, the first as a result of failing a doping test at an Olympic Games?',
    'Hans Gunnar Liljenwall - Alchetron, The Free Social Encyclopedia I Love to read n write about Interesting People Hans Gunnar Liljenwall Role\xa0\xa0Olympic athlete Born\xa0\xa09 July 1941 (age\xa074) (1941-07-09) Hans-Gunnar Liljenwall (born 9 July 1941) is a Swedish modern pentathlete who caused the disqualification of the Swedish men\'s team at the 1968 Summer Olympics held in Mexico City for his alcohol use. Liljenwall was the first athlete to be disqualified at the Olympics for drug use, following the introduction of anti-doping regulations by the International Olympic Committee in 1967. Sponsored Links Liljenwall reportedly had "two beers" to calm his nerves before the pistol shooting portion of the modern pentathlon. The Swedish team eventually had to return their bronze medals.',
    'Erstwhile | Definition of Erstwhile by Merriam-Webster Examples of erstwhile in a sentence <there\'s now a store where erstwhile lay green and pleasant pastures> Did You Know? The adverb erstwhile has been part of English since the 16th century, but it is formed from two words that are much older. It comes from the Old English words ær, meaning "early," and hwīl, which has much the same meaning as the modern word while. (The English word ere, meaning "before," is also descendant of ær.) The adjective erstwhile, as in erstwhile enemies, joined the language around 1900. 1569 First Known Use of erstwhile 1569',
]
embeddings = model.encode(sentences)
print(embeddings.shape)
# [3, 1536]

# Get the similarity scores for the embeddings
similarities = model.similarity(embeddings, embeddings)
print(similarities.shape)
# [3, 3]

Evaluation

Metrics

Semantic Similarity

Metric Value
pearson_cosine 0.9161
spearman_cosine 0.9257
pearson_manhattan 0.928
spearman_manhattan 0.9245
pearson_euclidean 0.9289
spearman_euclidean 0.9252
pearson_dot 0.9064
spearman_dot 0.9074
pearson_max 0.9289
spearman_max 0.9257

Binary Classification

Metric Value
cosine_accuracy 0.7148
cosine_accuracy_threshold 0.8047
cosine_f1 0.6311
cosine_f1_threshold 0.6595
cosine_precision 0.5439
cosine_recall 0.7514
cosine_ap 0.608
dot_accuracy 0.7227
dot_accuracy_threshold 816.7736
dot_f1 0.621
dot_f1_threshold 640.6546
dot_precision 0.4932
dot_recall 0.8382
dot_ap 0.6005
manhattan_accuracy 0.7188
manhattan_accuracy_threshold 758.1986
manhattan_f1 0.6271
manhattan_f1_threshold 839.9866
manhattan_precision 0.5323
manhattan_recall 0.763
manhattan_ap 0.6045
euclidean_accuracy 0.7207
euclidean_accuracy_threshold 24.5048
euclidean_f1 0.6253
euclidean_f1_threshold 26.8123
euclidean_precision 0.5325
euclidean_recall 0.7572
euclidean_ap 0.6046
max_accuracy 0.7227
max_accuracy_threshold 816.7736
max_f1 0.6311
max_f1_threshold 839.9866
max_precision 0.5439
max_recall 0.8382
max_ap 0.608

Binary Classification

Metric Value
cosine_accuracy 0.6816
cosine_accuracy_threshold 0.7124
cosine_f1 0.701
cosine_f1_threshold 0.5616
cosine_precision 0.5896
cosine_recall 0.8644
cosine_ap 0.7202
dot_accuracy 0.6738
dot_accuracy_threshold 685.1819
dot_f1 0.6969
dot_f1_threshold 513.6511
dot_precision 0.5643
dot_recall 0.911
dot_ap 0.6897
manhattan_accuracy 0.6816
manhattan_accuracy_threshold 807.0958
manhattan_f1 0.6993
manhattan_f1_threshold 923.9697
manhattan_precision 0.5815
manhattan_recall 0.8771
manhattan_ap 0.7263
euclidean_accuracy 0.6855
euclidean_accuracy_threshold 25.7451
euclidean_f1 0.6987
euclidean_f1_threshold 30.0132
euclidean_precision 0.5734
euclidean_recall 0.8941
euclidean_ap 0.7272
max_accuracy 0.6855
max_accuracy_threshold 807.0958
max_f1 0.701
max_f1_threshold 923.9697
max_precision 0.5896
max_recall 0.911
max_ap 0.7272

Training Details

Training Datasets

negation-triplets

  • Dataset: negation-triplets
  • Size: 5,025 training samples
  • Columns: anchor, entailment, and negative
  • Approximate statistics based on the first 1000 samples:
    anchor entailment negative
    type string string string
    details
    • min: 5 tokens
    • mean: 22.27 tokens
    • max: 91 tokens
    • min: 5 tokens
    • mean: 13.77 tokens
    • max: 42 tokens
    • min: 5 tokens
    • mean: 14.08 tokens
    • max: 42 tokens
  • Samples:
    anchor entailment negative
    A white kitty cat sitting on a bike seat. a cat on top of a bike parked indoors a cat underneath a bike parked indoors
    A bathroom with a sink and toilet and a bowl on the counter. A glass sink that is under a faucet. A glass sink that is not under a faucet.
    Seven people are jumping in the air, along the shore. People at the shore are jumping in the air. People at the shore are not jumping in the air.
  • Loss: CachedGISTEmbedLoss with these parameters:
    {'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': 0.025}
    

vitaminc-pairs

  • Dataset: vitaminc-pairs at be6febb
  • Size: 5,025 training samples
  • Columns: claim and evidence
  • Approximate statistics based on the first 1000 samples:
    claim evidence
    type string string
    details
    • min: 6 tokens
    • mean: 16.21 tokens
    • max: 45 tokens
    • min: 9 tokens
    • mean: 37.01 tokens
    • max: 187 tokens
  • Samples:
    claim evidence
    Boss Key Productions is yet to release the BlueStreak video game . BlueStreak is an upcoming video game developed by Boss Key Productions and published by Nexon .
    Jay-Z appeared on Blue Ivy 's first two albums . Jay-Z appeared on Blue Ivy 's first two albums as well , and the two frequently collaborated .
    The film was reviewed by more than 140 critics . On review aggregator Rotten Tomatoes , the film has an approval rating of 80 % based on 142 reviews , with an average rating of 7.1/10 .
  • Loss: CachedGISTEmbedLoss with these parameters:
    {'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': 0.025}
    

scitail-pairs-qa

  • Dataset: scitail-pairs-qa at 0cc4353
  • Size: 5,025 training samples
  • Columns: sentence1 and sentence2
  • Approximate statistics based on the first 1000 samples:
    sentence1 sentence2
    type string string
    details
    • min: 7 tokens
    • mean: 15.97 tokens
    • max: 41 tokens
    • min: 6 tokens
    • mean: 15.15 tokens
    • max: 33 tokens
  • Samples:
    sentence1 sentence2
    The cytoskeleton is the skeleton of the cell. What is the skeleton of the cell?
    Muscular dystrophy is a a wasting disease. What type of disease is muscular dystrophy?
    A pumpkin is a fruit. Which food is a fruit?
  • Loss: CachedGISTEmbedLoss with these parameters:
    {'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': 0.025}
    

scitail-pairs-pos

  • Dataset: scitail-pairs-pos at 0cc4353
  • Size: 5,025 training samples
  • Columns: sentence1 and sentence2
  • Approximate statistics based on the first 1000 samples:
    sentence1 sentence2
    type string string
    details
    • min: 7 tokens
    • mean: 23.62 tokens
    • max: 68 tokens
    • min: 7 tokens
    • mean: 15.74 tokens
    • max: 40 tokens
  • Samples:
    sentence1 sentence2
    There have been five mass extinctions in Earth's history. Five mass distinctions have radically altered the history of life.
    The ultimate source of energy for life on Earth is the sun. Ultimately, most life forms get their energy from the sun.
    N Neurotransmitter Any one of numerous chemicals in the nervous system that modify or result in the transmission of nerve impulses between synapses. Like a runner passing a baton, the transmission of nerve impulses between neurons depends on neurotransmitters.
  • Loss: CachedGISTEmbedLoss with these parameters:
    {'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': 0.025}
    

xsum-pairs

  • Dataset: xsum-pairs
  • Size: 5,025 training samples
  • Columns: summary and document
  • Approximate statistics based on the first 1000 samples:
    summary document
    type string string
    details
    • min: 8 tokens
    • mean: 25.63 tokens
    • max: 47 tokens
    • min: 45 tokens
    • mean: 211.46 tokens
    • max: 371 tokens
  • Samples:
    summary document
    Rising British star Hannah Barnes will ride for the newly-formed Canyon//SRAM team in next year's inaugural UCI Women's WorldTour circuit. Barnes, who has spent two seasons with American team UHC-Healthcare, won the white jersey for the best young rider at this year's Women's Tour.
    "It's been really good in America but I'm happy to come back to Europe," said the 22-year-old from Northamptonshire.
    "My whole goal for 2015 was to get some good results and then come back here."
    Joining Barnes on the team are the overall winner of the Women's Tour, German time trial star Lisa Brennauer, and RideLondon Grand Prix winner, Italy's Barbara Guarischi.
    The team will ride the full 17-race Women's WorldTour calendar in 2016.
    Germany's Canyon will supply the bike frames, with American firm SRAM providing the components.
    The team's nine riders, from six countries, will wear kit from British company Rapha, which has recently announced it will no longer be supplying elite men's outfit Team Sky after 2016.
    The team will begin its 2016 season when Tiffany Cromwell rides in the Australian national championships in January, with the first full race being the Ladies Tour of Qatar in February.
    Helping riders qualify for the Rio Olympics will be a focus for the team, as will the big American races, the Tour of California and Philadelphia Cycling Classic, as well as Britain's Women's Tour and the women's race at the Tour de France, La Course.
    "My main goal for the year is to make the team for the Olympics but with this injury I don't really know," said Barnes, who broke her ankle in August.
    "I'd like to go back to California and do the Tour there too."
    A doctor was injured when a prisoner tried to escape during a routine medical appointment at a hospital in North Lanarkshire. The 31-year-old inmate from HMP Shotts was being escorted by G4S security staff when he tried to get away.
    A doctor who tried to assist the security staff suffered minor injuries during the incident on Friday.
    The Scottish Prison Service said an investigation had begun into what happened.
    A spokesman said: "I can confirm there was an incident involving a prisoner from HMP Shotts at Wishaw General Hospital today.
    "We will be working with Police Scotland in investigating the full circumstances of the incident."
    A G4S spokesman said: "During a routine hospital appointment a prisoner attempted to evade custody but was immediately apprehended by G4S staff.
    "The prompt actions of our officers averted a more serious incident and demonstrates the challenging situations our staff can face while carrying out their duties."
    West Ham winger Michail Antonio has been ruled out for the rest of the season with a "significant injury", manager Slaven Bilic says. The 27-year-old was injured in the Hammers' 1-0 win over Swansea at London Stadium last weekend.
    "It's a significant injury and he's out for the season," Bilic confirmed.
    Antonio, who has scored nine goals for the Hammers this season, was called up by England for the first time in August.
    "It is a big blow. We know what he has been giving. He is one of our best players," Bilic added.
    He was again called up for England's World Cup qualifier against Lithuania last month but pulled out of the squad with a hamstring injury and has yet to make his international debut.
    He joined West Ham from Nottingham Forest in 2015 and signed a new four-year deal with the club last summer.
  • Loss: CachedGISTEmbedLoss with these parameters:
    {'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': 0.025}
    

sciq_pairs

  • Dataset: sciq_pairs at 2c94ad3
  • Size: 5,025 training samples
  • Columns: sentence1 and sentence2
  • Approximate statistics based on the first 1000 samples:
    sentence1 sentence2
    type string string
    details
    • min: 7 tokens
    • mean: 16.81 tokens
    • max: 45 tokens
    • min: 2 tokens
    • mean: 83.54 tokens
    • max: 512 tokens
  • Samples:
    sentence1 sentence2
    What chemical affects the onset of puberty and duration? Puberty lasts from about ages 12 to 18 years and is controlled by hormones.
    Within the chloroplast, synthesis of what takes place in the fluid inside the inner membrane called the stroma? Figure 4.17 The chloroplast has an outer membrane, an inner membrane, and membrane structures called thylakoids that are stacked into grana. The space inside the thylakoid membranes is called the thylakoid space. The light harvesting reactions take place in the thylakoid membranes, and the synthesis of sugar takes place in the fluid inside the inner membrane, which is called the stroma. Chloroplasts also have their own genome, which is contained on a single circular chromosome.
    What type of scientist uses earth-orbiting telescopes? Astronomers use many tools to study things in space. Earth-orbiting telescopes view stars and galaxies from the darkness of space ( Figure below ). They may have optical and radio telescopes to see things that the human eye can't see. Spacecraft travel great distances to send back information on faraway places.
  • Loss: CachedGISTEmbedLoss with these parameters:
    {'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': 0.025}
    

qasc_pairs

  • Dataset: qasc_pairs at a34ba20
  • Size: 5,025 training samples
  • Columns: sentence1 and sentence2
  • Approximate statistics based on the first 1000 samples:
    sentence1 sentence2
    type string string
    details
    • min: 5 tokens
    • mean: 11.37 tokens
    • max: 25 tokens
    • min: 13 tokens
    • mean: 33.52 tokens
    • max: 64 tokens
  • Samples:
    sentence1 sentence2
    What can help decrease emissions? carpooling decreases the amount of cars used to travel to a place. Cars and gasoline-burning engines are large sources of emissions.
    Carpooling decreases emissions
    What can antibodies (large Y-shaped proteins) recognize and bind to? Antibodies are large, Y-shaped proteins that recognize and bind to antigens.. ALL immunogens are antigens.
    Antibodies are large, Y-shaped proteins that can recognize and bind to immunogens
    What process is needed to support a baby in the womb? Oxygen is essential for cellular respiration for all aerobic organisms.. Less oxygen for the mother means less oxygen for the baby.
    Mothers need respiration for their babies.
  • Loss: CachedGISTEmbedLoss with these parameters:
    {'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': 0.025}
    

openbookqa_pairs

  • Dataset: openbookqa_pairs
  • Size: 3,029 training samples
  • Columns: question and fact
  • Approximate statistics based on the first 1000 samples:
    question fact
    type string string
    details
    • min: 3 tokens
    • mean: 13.89 tokens
    • max: 65 tokens
    • min: 5 tokens
    • mean: 11.54 tokens
    • max: 31 tokens
  • Samples:
    question fact
    A prickly pear absorbs nutrients from plants absorb nutrients from soil into themselves through their roots
    When it's summer in the USA it's winter June is during the winter in the southern hemisphere
    To move electrical energy around a field, a person would use metal is an electrical energy conductor
  • Loss: CachedGISTEmbedLoss with these parameters:
    {'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': 0.025}
    

msmarco_pairs

  • Dataset: msmarco_pairs at 28ff31e
  • Size: 5,025 training samples
  • Columns: sentence1 and sentence2
  • Approximate statistics based on the first 1000 samples:
    sentence1 sentence2
    type string string
    details
    • min: 4 tokens
    • mean: 8.59 tokens
    • max: 25 tokens
    • min: 15 tokens
    • mean: 75.16 tokens
    • max: 208 tokens
  • Samples:
    sentence1 sentence2
    is switzerland expensive Hi Im Swiss and I can answer your question. For us Swiss people Switzerland is not that expensive because out salary makes up for it (we have one of the highest salaries per/person worldwide). For foreigners visiting Switzerland many will find it very expensive, from public transportation to food.
    what does dhea sulfate do for women DHEA, DHEA-S. This test measures the level of dehydroepiandrosterone (DHEA) and dehydroepiandrosterone sulfate (DHEA-S) in your blood. It may also be used to check how well your adrenal glands are working. DHEA is a hormone made by your adrenal glands and to a lesser degree by the ovaries and testes. DHEA is changed into DHEA-S in your adrenal glands and liver. In both men and women, the sex hormones estrogen and testosterone depend on DHEA. DHEA also has a role in the making of insulin growth factor-1 (IGF-1).
    how long do i need to keep tax returns After filing your late taxes, remember you will keep your tax return three years from the date you file rather than three years from that tax year. For those that have old tax returns on file, don’t be in a rush to shred them. While fall cleaning, organize and file away tax returns.
  • Loss: CachedGISTEmbedLoss with these parameters:
    {'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': 0.025}
    

nq_pairs

  • Dataset: nq_pairs at f9e894e
  • Size: 5,025 training samples
  • Columns: sentence1 and sentence2
  • Approximate statistics based on the first 1000 samples:
    sentence1 sentence2
    type string string
    details
    • min: 10 tokens
    • mean: 11.81 tokens
    • max: 25 tokens
    • min: 19 tokens
    • mean: 129.07 tokens
    • max: 512 tokens
  • Samples:
    sentence1 sentence2
    who owns the rights to call of duty Call of Duty The Call of Duty games are published and owned by Activision. While Infinity Ward is still a developer, Treyarch and Sledgehammer Games also develop several of the titles with the release of the studios' games alternating with each other. Some games have been developed by Gray Matter Interactive, Nokia, Exakt Entertainment, Spark Unlimited, Amaze Entertainment, n-Space, Aspyr, Rebellion Developments, Ideaworks Game Studio, and nStigate Games. The games use a variety of engines, including the id Tech 3, the Treyarch NGL, and the IW engine.
    who sings i wanna get next to you I Wanna Get Next to You "I Wanna Get Next to You" is a 1976 soul single written, composed and produced by American songwriter and producer Norman Whitfield, and most famously sung by American R&B band Rose Royce. It is the third official single from the Car Wash soundtrack. The song has also become a staple on oldies radio and on adult contemporary stations.
    when was the birth control pill made available Birth control In 1909, Richard Richter developed the first intrauterine device made from silkworm gut, which was further developed and marketed in Germany by Ernst Gräfenberg in the late 1920s.[152] In 1951, a chemist, named Carl Djerassi from Mexico City made the hormones in progesterone pills using Mexican yams.[153] Djerassi had chemically created the pill but was not equipped to distribute it to patients. Meanwhile, Gregory Pincus and John Rock with help from the Planned Parenthood Federation of America developed the first birth control pills in the 1950s, such as mestranol/noretynodrel, which became publicly available in the 1960s through the Food and Drug Administration under the name Enovid.[146][154] Medical abortion became an alternative to surgical abortion with the availability of prostaglandin analogs in the 1970s and mifepristone in the 1980s.[155]
  • Loss: CachedGISTEmbedLoss with these parameters:
    {'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': 0.025}
    

trivia_pairs

  • Dataset: trivia_pairs at a7c36e3
  • Size: 5,025 training samples
  • Columns: query and answer
  • Approximate statistics based on the first 1000 samples:
    query answer
    type string string
    details
    • min: 8 tokens
    • mean: 16.85 tokens
    • max: 55 tokens
    • min: 15 tokens
    • mean: 202.22 tokens
    • max: 411 tokens
  • Samples:
    query answer
    What famous London building is officially called 1 Canada Square? One Canada Square, London, England Tourist Information Locals and travelers to connect with About London Borough of Tower Hamlets, London, England 51.505-0.0196 One Canada Square (often incorrectly called Canary Wharf , after its location) is a skyscraper in Canary Wharf, London . It was the tallest building in the United Kingdom from 1990 to 2010, standing at 235 metres (770 ft) above ground level and containing 50 storeys. In late 2010, it was surpassed by The Shard (completed in July 2012) which stands at 309.6 metres (1,016 ft). One Canada Square was designed by principal architect Cesar Pelli, who based the design and shape mainly on the World Financial Center and the Elizabeth Tower. The building is clad with expensive stainless steel. One of the predominant features of the building is the pyramid roof which contains a flashing aircraft warning light, a rare feature for buildings in the United Kingdom. The distinctive pyramid pinnacle is at 240 metres (800 ft) above sea level. One Canada Square is primarily used for offices, though there are some retail units on the lower ground floor. It is a prestigious location for offices and as of January 2013 was 100% let. The building is recognised as a London landmark and it has gained much attention through film, television and other media when its status was the tallest building in the United Kingdom and continues to gain attention. Map
    Who is the patron saint of dentists? St. Apollonia - Saints & Angels - Catholic Online Saints & Angels Author and Publisher - Catholic Online Facts Take the Saints Trivia Quiz now! St. Apollonia, who died in the year 249, was martyred for not renouncing her faith during the reign of Emperor Philip. The account of the life of St. Apollonia was written by St. Dionysius to Fabian, Bishop of Antioch. Apollonia had all her teeth knocked out after being hit in the face by a Christian persecutor under the reign of Emperor Philip. After she was threatened with fire unless she renounced her faith, Apollonia jumped into the flames voluntarily. She is considered the patron of dental diseases and is often invoked by those with toothaches. Ancient art depicts her with a golden tooth at the end of her necklace. Also in art, she is seen with pincers holding a tooth.
    Which country has the international vehicle registration CDN? Why does Canada have the letters CDN as its international car registration plate? Surely it would be more logical to have CND?
  • Loss: CachedGISTEmbedLoss with these parameters:
    {'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': 0.025}
    

gooaq_pairs

  • Dataset: gooaq_pairs at b089f72
  • Size: 5,025 training samples
  • Columns: sentence1 and sentence2
  • Approximate statistics based on the first 1000 samples:
    sentence1 sentence2
    type string string
    details
    • min: 8 tokens
    • mean: 11.43 tokens
    • max: 21 tokens
    • min: 13 tokens
    • mean: 55.2 tokens
    • max: 126 tokens
  • Samples:
    sentence1 sentence2
    what are fettuccine used for? Long flattish noodle-shaped pasta, similar to tagliatelle. A very good pasta to serve with oil or butter-based sauces, as the sauce goes a long way, coats the pasta evenly and also helps to prevent the strands of pasta from clumping together.
    can you drink lemon water after brushing teeth? DO NOT brush your teeth for at least 30 minutes after drinking the lemon water. Use a soft toothbrush and fluoridated toothpaste (fluoride toughens your enamel) and do not brush aggressively. Acid softens the enamel and makes it more prone to erosion during brushing.
    is ui ux front end? User experience (UX) design is centered around the satisfaction the user experiences with your software. Front-end development is the technical implementation of the software's user interface (UI). UI design is the graphical bridge that connects the two.
  • Loss: CachedGISTEmbedLoss with these parameters:
    {'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': 0.025}
    

paws-pos

  • Dataset: paws-pos at 161ece9
  • Size: 5,025 training samples
  • Columns: sentence1 and sentence2
  • Approximate statistics based on the first 1000 samples:
    sentence1 sentence2
    type string string
    details
    • min: 10 tokens
    • mean: 25.54 tokens
    • max: 51 tokens
    • min: 10 tokens
    • mean: 25.51 tokens
    • max: 50 tokens
  • Samples:
    sentence1 sentence2
    A railway station of the same name on the Golitsyno -- Minsk railway , is located in Moscow . A railway station of the same name on the Golitsyno -- Minsk railway line is located in Moscow .
    To calculate such a point mass , an integration is carried out over the entire range of the continuous variable , on the probability density of the random part . In order to calculate such a point mass , an integration over the entire range of continuous size is carried out on the probability density of the random part .
    It also has representation at the local and regional level . It also has a representation at regional and local level .
  • Loss: CachedGISTEmbedLoss with these parameters:
    {'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': 0.025}
    

global_dataset

  • Dataset: global_dataset
  • Size: 36,293 training samples
  • Columns: sentence1 and sentence2
  • Approximate statistics based on the first 1000 samples:
    sentence1 sentence2
    type string string
    details
    • min: 4 tokens
    • mean: 29.83 tokens
    • max: 328 tokens
    • min: 2 tokens
    • mean: 52.56 tokens
    • max: 479 tokens
  • Samples:
    sentence1 sentence2
    An autotroph ( from Greek autos = self and trophe = nutrition ) is an organism that makes organic compounds from simple molecules . The word autotroph comes from the Greek autos = self and trophe = nutrition , related to trephein = to make solid , congeal , thicken
    Nonrenewable resources cannot be replaced as easily as it is consumed. What type of resource cannot be replaced as easily as it is consumed?
    The data included email addresses and passwords that had been stored without any protection, a security firm said.
    Leaked Source said the massive cache of credentials dated from 2012 but had only now been leaked and put online.
    And it had come from a hacker who had supplied security firms with 43 million user names from music service Last.fm.
    Rambler has been described as the Russian equivalent of Yahoo as it offers email services as well as acting as a news and content hub for its users.
    "We know about that database," said the service in a statement.
    "It was leaked March 2014 and contained millions of accounts. Right after the accident we forced our users to change their passwords.
    "We also have forbidden to use the previously used passwords for the same account."
    Leaked Source broke the news about the breach and said it had verified some of the data with the help of Russian journalists. .
    Leaked Source said passwords associated with login names had been stored with "no encryption or hashing". Instead, it said, they had been listed in plain text.
    Analysis of the long list of passwords showed that "asdasd" was the most popular string, used by more than 723,000 people, it said.
    The second most popular password among the 98 million users was "asdasd123".
    In June this year, details of more than 100 million users of the Russian VK.com service were shared online.
    Copies of the long list of login names and passwords was offered online at a price of one bitcoin (£456).
    Login names and passwords for more than 98 million users of the Russian Rambler.ru email service have reportedly been stolen and put online.
  • Loss: CachedGISTEmbedLoss with these parameters:
    {'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': 0.025}
    

Evaluation Datasets

vitaminc-pairs

  • Dataset: vitaminc-pairs at be6febb
  • Size: 128 evaluation samples
  • Columns: claim and evidence
  • Approximate statistics based on the first 1000 samples:
    claim evidence
    type string string
    details
    • min: 9 tokens
    • mean: 19.71 tokens
    • max: 38 tokens
    • min: 9 tokens
    • mean: 32.5 tokens
    • max: 78 tokens
  • 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 with these parameters:
    {'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': 0.025}
    

negation-triplets

  • Dataset: negation-triplets
  • Size: 128 evaluation samples
  • Columns: anchor, entailment, and negative
  • Approximate statistics based on the first 1000 samples:
    anchor entailment negative
    type string string string
    details
    • min: 8 tokens
    • mean: 14.11 tokens
    • max: 46 tokens
    • min: 6 tokens
    • mean: 12.27 tokens
    • max: 18 tokens
    • min: 6 tokens
    • mean: 12.65 tokens
    • max: 19 tokens
  • Samples:
    anchor entailment negative
    a bike leaning on a metal fence next to some flowing water. A bicycle parked next to a flooded river A bicycle parked far away from a flooded river.
    A woman is painting a mural of a woman's face. There is a woman painting. There is no woman painting.
    A woman sitting at a table while holding a pair of scissors. A woman smiles and holds up a pair of scissors. A woman frowns and puts down a pair of scissors.
  • Loss: CachedGISTEmbedLoss with these parameters:
    {'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': 0.025}
    

scitail-pairs-pos

  • Dataset: scitail-pairs-pos at 0cc4353
  • Size: 128 evaluation samples
  • Columns: sentence1 and sentence2
  • Approximate statistics based on the first 1000 samples:
    sentence1 sentence2
    type string string
    details
    • min: 9 tokens
    • mean: 20.13 tokens
    • max: 53 tokens
    • min: 8 tokens
    • mean: 15.48 tokens
    • max: 23 tokens
  • 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 with these parameters:
    {'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': 0.025}
    

scitail-pairs-qa

  • Dataset: scitail-pairs-qa at 0cc4353
  • Size: 128 evaluation samples
  • Columns: sentence1 and sentence2
  • Approximate statistics based on the first 1000 samples:
    sentence1 sentence2
    type string string
    details
    • min: 7 tokens
    • mean: 16.09 tokens
    • max: 41 tokens
    • min: 9 tokens
    • mean: 14.87 tokens
    • max: 28 tokens
  • Samples:
    sentence1 sentence2
    The field of study known as mathematics is called the language of science. What field of study is called the language of science?
    Roots grow in length and width from the primary and secondary meristem. Roots grow in length and width from the primary and secondary what?
    Muscle groups are controlled by the motor cortex . Muscle groups are controlled by what mechanism?
  • Loss: CachedGISTEmbedLoss with these parameters:
    {'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': 0.025}
    

xsum-pairs

  • Dataset: xsum-pairs
  • Size: 128 evaluation samples
  • Columns: summary and document
  • Approximate statistics based on the first 1000 samples:
    summary document
    type string string
    details
    • min: 14 tokens
    • mean: 25.09 tokens
    • max: 39 tokens
    • min: 58 tokens
    • mean: 230.7 tokens
    • max: 342 tokens
  • Samples:
    summary document
    A diamond ring that belonged to former child star Shirley Temple is going up for auction next month at a starting price of $25m (£17.3m), Sotheby's says. The auction house said the 9.54-carat "Fancy Deep Blue" ring was bought by Temple's father in 1940 for $7,210.
    Temple, one of Hollywood's most popular stars in the 1930s, died in 2014 at the age of 85.
    A private buyer bought the ring from her estate and is now putting it up for auction, Sotheby's said.
    It is estimated to be worth up to $35 million.
    Temple pursued a career in politics after leaving the entertainment industry, serving as US ambassador to Ghana and Czechoslovakia.
    A selection of her belongings, including a dress worn at the 1935 Oscars, has previously been auctioned off by her family.
    A cybersecurity researcher working for anti-virus firm Kaspersky Lab in Russia has been arrested. Ruslan Stoyanov, a member of Kasperksy's investigations team, was arrested in December but news of his apprehension has only just surfaced.
    He was arrested as part of an investigation into payments he allegedly received from foreign firms.
    At Kaspersky, Mr Stoyanov helped look into hack attacks and breaches at Russian companies.
    In a statement, Kaspkersy Lab said the arrest had nothing to do with his work for the security firm.
    "Ruslan Stoyanov is under investigation for a period predating his employment at Kaspersky Lab," said the company in a statement. Mr Stoyanov joined Kaspersky in 2012.
    It added: "We do not possess details of the investigation."
    Prior to working for Kaspersky, Mr Stoyanov was employed at other security firms. From 2000 to 2006 he was a major in the Russian Ministry of Interior's Moscow cybercrime unit.
    Information about the reasons for the arrest are scant, but one Russian newspaper linked it to a probe into Sergei Mikhailov - a senior official at Russia's FSB intelligence service.
    Forbes reported that Mr Stoyanov has been arrested under Article 275 of Russia's criminal code which lets prosecutors charge people for treason for "providing financial, technical, advisory, or other assistance" to other countries or non-Russian organisations seen as hostile.
    Scotland's Russell Knox won the Travelers Championship after Jim Furyk became the first player in PGA Tour history to shoot a round of 58. Knox, 31, closed with a two-under 68 to beat Jerry Kelly by one shot.
    Daniel Berger went into the final round as leader but carded a four-over-par 74 to end tied for fifth with Furyk, Robert Garrigus and Tyrone van Aswegen.
    American Furyk, 46, carded 10 birdies and an eagle in his bogey-free round of 12 under par to finish on 11 under.
    Knox, who also won in Shanghai in November 2015, becomes the fifth player to have multiple wins in the 2015-16 PGA Tour season.
    The others are the current top three players in the world - Jason Day, Dustin Johnson and Jordan Spieth - and world number eight Adam Scott.
    The victory lifts the Scot into contention for at least a wildcard place in the European Ryder Cup team for the biennial tournament against the United States, which takes place at the end of September.
    "It's been an incredible year for me," said Knox.
    "I keep believing in myself, I tell myself every day that I'm good enough to be up there and win tournaments. It's been an enjoyable ride."
    Set to move inside the top 20 in the world rankings, he added that winning this tournament would make it difficult for European captain Darren Clarke "not to pick me".
    Furyk, who was already one of only six men to have recorded a score of 59 for 18 holes, said: "A million and a half rounds played in the history of the PGA Tour and you look at the great names ahead of me.
    "It's humbling. To stand alone at 58 is really a cool accomplishment."
  • Loss: CachedGISTEmbedLoss with these parameters:
    {'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': 0.025}
    

sciq_pairs

  • Dataset: sciq_pairs at 2c94ad3
  • Size: 128 evaluation samples
  • Columns: sentence1 and sentence2
  • Approximate statistics based on the first 1000 samples:
    sentence1 sentence2
    type string string
    details
    • min: 7 tokens
    • mean: 16.28 tokens
    • max: 37 tokens
    • min: 2 tokens
    • mean: 72.52 tokens
    • max: 400 tokens
  • Samples:
    sentence1 sentence2
    Internal resistance, or (electrical) resistance in general, involves the resistance of the flow of what? Internal Resistance As noted before, a 12-V truck battery is physically larger, contains more charge and energy, and can deliver a larger current than a 12-V motorcycle battery. Both are lead-acid batteries with identical emf, but, because of its size, the truck battery has a smaller internal resistance r . Internal resistance is the inherent resistance to the flow of current within the source itself. Figure 21.9 is a schematic representation of the two fundamental parts of any voltage source. The emf (represented by a script E in the figure) and internal resistance r are in series. The smaller the internal resistance for a given emf, the more current and the more power the source can supply.
    If a solute is a gas, increasing the temperature will do what? If a solute is a gas, increasing the temperature decreases its solubility. For example, less carbon dioxide can dissolve in warm ocean water than in cold ocean water.
    What are usually planted in rows with bare soil in between the rows? The problem doesn’t stop with plowing. Crops are usually planted in rows with bare soil in between the rows. In places where crops grow only during part of the year, the land may be bare for a few months.
  • Loss: CachedGISTEmbedLoss with these parameters:
    {'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': 0.025}
    

qasc_pairs

  • Dataset: qasc_pairs at a34ba20
  • Size: 128 evaluation samples
  • Columns: sentence1 and sentence2
  • Approximate statistics based on the first 1000 samples:
    sentence1 sentence2
    type string string
    details
    • min: 6 tokens
    • mean: 11.02 tokens
    • max: 21 tokens
    • min: 17 tokens
    • mean: 33.07 tokens
    • max: 60 tokens
  • Samples:
    sentence1 sentence2
    What kind of organism use cellulose for their cell walls? Plants use cellulose for their cell walls.. If the plant is green, it is a producer.
    Producers use cellulose for their cell walls.
    Energy enters what in the form of sunlight or chemical compounds. Energy enters ecosystems in the form of sunlight or chemical compounds.. Biomes are global ecosystems.
    Energy enters biomes in the form of sunlight or chemical compounds.
    What does heat and pressure change into natural gas? heat and pressure change the remains of prehistoric living things into natural gas. Dinosaurs and Other Prehistoric Creatures Dinosaurs are just one group of prehistoric animals.
    heat and pressure change the remains of dinosaurs into natural gas
  • Loss: CachedGISTEmbedLoss with these parameters:
    {'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': 0.025}
    

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
    • min: 3 tokens
    • mean: 13.96 tokens
    • max: 47 tokens
    • min: 4 tokens
    • mean: 11.78 tokens
    • max: 28 tokens
  • 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 with these parameters:
    {'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': 0.025}
    

msmarco_pairs

  • Dataset: msmarco_pairs at 28ff31e
  • Size: 128 evaluation samples
  • Columns: sentence1 and sentence2
  • Approximate statistics based on the first 1000 samples:
    sentence1 sentence2
    type string string
    details
    • min: 4 tokens
    • mean: 8.45 tokens
    • max: 20 tokens
    • min: 29 tokens
    • mean: 72.06 tokens
    • max: 227 tokens
  • Samples:
    sentence1 sentence2
    how long is flight from vegas to california Flying time from Las Vegas, NV to Los Angeles, CA. The total flight duration from Las Vegas, NV to Los Angeles, CA is 41 minutes. This is the average in-air flight time (wheels up to wheels down on the runway) based on actual flights taken over the past year, including routes like LAS to LAX.
    tangible net worth calculation meaning A measure of the physical worth of a company, which does not include any value derived from intangible assets such as copyrights, patents and intellectual property. Tangible net worth is calculated by taking a firm's total assets and subtracting the value of all liabilities and intangible assets.Next Up.REAKING DOWN 'Tangible Net Worth'. In terms of a consumer, tangible net worth is the sum of all your tangible assets (cash, home, cars, etc) less any liabilities you may have.
    who is father ferdinand Ferdinand does indeed fall in love with Prospero's daughter Miranda, aided by the magic of Ariel. Prospero does also have a plan for Ferdinand, which is for him to marry his daughter and cement the reconciliation between Prospero, right Duke of Milan and Alonso, Ferdinand's father and King of Milan. It is interesting to note that Ferdinand is presented as more passive than his romantic counterpart, Miranda.
  • Loss: CachedGISTEmbedLoss with these parameters:
    {'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': 0.025}
    

nq_pairs

  • Dataset: nq_pairs at f9e894e
  • Size: 128 evaluation samples
  • Columns: sentence1 and sentence2
  • Approximate statistics based on the first 1000 samples:
    sentence1 sentence2
    type string string
    details
    • min: 10 tokens
    • mean: 11.92 tokens
    • max: 22 tokens
    • min: 27 tokens
    • mean: 133.38 tokens
    • max: 416 tokens
  • Samples:
    sentence1 sentence2
    who owns the rights to guns and roses Guns N' Roses Slash was replaced by Nine Inch Nails touring guitarist Robin Finck in January 1997, who signed a two-year contract with the band in August 1997, making him an official member.[130] Finck was originally recommended by Matt Sorum to Rose a year earlier as a possible second guitarist to complement Slash.[122] Slash's departure was followed shortly thereafter by Matt Sorum in April 1997, who was fired by Rose after getting in an argument about Tobias's inclusion in the band.[131] Sorum later stated Tobias was the "Yoko Ono of Guns N' Roses".[122] McKagan was the last of the Appetite lineup to leave, resigning as bassist in August 1997.[132] McKagan had recently become a father and wrote about his decision to leave in his autobiography, stating "Guns had been paying rent on studios for three years now—from 1994 to 1997—and still did not have a single song. The whole operation was so erratic that it didn't seem to fit with my hopes for parenthood, for stability."[132] McKagan was replaced later that year by former Replacements bassist Tommy Stinson.[133] An actual break-up of Guns N' Roses never occurred, as new players were brought in as the old ones left. Rose reportedly purchased the full rights to the Guns N' Roses name in 1997.[129][134] Slash claimed he and bandmates signed over the name in duress, stating "Axl refused to go onstage one night during the Use Your Illusion tour in 1992 unless the band signed away the name rights to the band. Unfortunately, we signed it. I didn't think he'd go on stage otherwise."[135] Rose denied the claim, saying "(it) Never happened, all made up, fallacy and fantasy. Not one single solitary thread of truth to it. Had that been the case I would have been cremated years ago legally, could've cleaned me out for the name and damages. It's called under duress with extenuating circumstances."[135]
    what is red hot chili peppers otherside about Otherside "Otherside" refers to former band member Hillel Slovak, who died of a heroin overdose on June 25, 1988. The song talks about his struggles from this addiction.[1]
    when do you have to pay death duties Estate tax in the United States If an asset is left to a spouse or a federally recognized charity, the tax usually does not apply. In addition, a maximum amount, varying year by year, can be given by an individual, before and/or upon their death, without incurring federal gift or estate taxes:[2] $5,340,000 for estates of persons dying in 2014[3] and 2015,[4] $5,450,000 (effectively $10.90 million per married couple) for estates of persons dying in 2016.[5] Because of these exemptions, it is estimated that only the largest 0.2% of estates in the U.S. will pay the tax.[6]
  • Loss: CachedGISTEmbedLoss with these parameters:
    {'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': 0.025}
    

trivia_pairs

  • Dataset: trivia_pairs at a7c36e3
  • Size: 128 evaluation samples
  • Columns: query and answer
  • Approximate statistics based on the first 1000 samples:
    query answer
    type string string
    details
    • min: 7 tokens
    • mean: 17.31 tokens
    • max: 40 tokens
    • min: 29 tokens
    • mean: 206.09 tokens
    • max: 385 tokens
  • Samples:
    query answer
    Which musical features the song Sit Down You’re Rockin’ The Boat? GUYS & DOLLS (Broadway) - "Sit Down, You're Rockin' the Boat" [LIVE @ The 2009 Tony Awards] - YouTube GUYS & DOLLS (Broadway) - "Sit Down, You're Rockin' the Boat" [LIVE @ The 2009 Tony Awards] 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. Published on Jun 19, 2013 The cast of the Broadway revival of the musical GUYS & DOLLS, perform the number "Sit Down, You're Rockin' the Boat" live at the 2009 Tony Awards Category
    "John Wayne played the lead role of whom in the 1958 film ""The Conqueror""?" The movie so toxic it killed John Wayne: the tragedy of The Conqueror The movie so toxic it killed John Wayne: the tragedy of The Conqueror John Wayne and Susan Hayward in The Conqueror Credit: Rex Chris Bell 17 January 2017 • 6:24pm The Duke playing Genghis Khan in yellowface, filming on a nuclear testing ground? Chris Bell on why nobody escaped the fallout from The Conqueror Towards the end of his life, Howard Hughes – the billionaire tycoon, aviator and filmmaker – had become a recluse. Locked in the penthouse suite at his Xanadu Princess Resort hotel in the Bahamas, he refused to bathe, cut his nails or hair, use a toilet or even open the curtains. Instead, he would sit for hours in his darkened bedroom, naked except for a pink hotel napkin, eating nothing but chocolate bars and chicken, surrounded by dozens of Kleenex boxes that he continuously stacked and rearranged.  But another ritual obsession would come dominate his final few months in 1976: two movies, played continually via a projector on the wall, that he watched over and over again. The first was his favourite film , Ice Station Zebra – Rock Hudson’s tense... Premium
    Which country has won the most soccer World Cups? Brazil may have won the most World Cup titles, but Germany has been the most consistent team
  • Loss: CachedGISTEmbedLoss with these parameters:
    {'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': 0.025}
    

gooaq_pairs

  • Dataset: gooaq_pairs at b089f72
  • Size: 128 evaluation samples
  • Columns: sentence1 and sentence2
  • Approximate statistics based on the first 1000 samples:
    sentence1 sentence2
    type string string
    details
    • min: 8 tokens
    • mean: 11.65 tokens
    • max: 18 tokens
    • min: 23 tokens
    • mean: 57.55 tokens
    • max: 129 tokens
  • Samples:
    sentence1 sentence2
    do nz residents need a visa to work in australia? Most NZ citizens can visit, live and work in Australia without applying for a tourist or work visa. NZ permanent residents need to apply for visas to Australia.
    is clep testing worth it? Money is a valuable resource, but time is even more valuable. CLEP tests can help you get a degree much faster than the traditional college path. The conventional amount of time to get an undergraduate degree is 4 years, though it can take many students as long as six years.
    does someone know if you block them on iphone? If you block someone, they do not receieve any notification that they have been blocked. The only way for them to know would be for you to tell them. Furthermore, if they send you an iMessage, it will say that it was delivered on their phone, so they won't even know that you're not seeing their message.
  • Loss: CachedGISTEmbedLoss with these parameters:
    {'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': 0.025}
    

paws-pos

  • Dataset: paws-pos at 161ece9
  • Size: 128 evaluation samples
  • Columns: sentence1 and sentence2
  • Approximate statistics based on the first 1000 samples:
    sentence1 sentence2
    type string string
    details
    • min: 10 tokens
    • mean: 25.58 tokens
    • max: 41 tokens
    • min: 10 tokens
    • mean: 25.4 tokens
    • max: 41 tokens
  • 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 with these parameters:
    {'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': 0.025}
    

global_dataset

  • Dataset: global_dataset
  • Size: 325 evaluation samples
  • Columns: sentence1 and sentence2
  • Approximate statistics based on the first 1000 samples:
    sentence1 sentence2
    type string string
    details
    • min: 5 tokens
    • mean: 31.63 tokens
    • max: 324 tokens
    • min: 2 tokens
    • mean: 58.18 tokens
    • max: 416 tokens
  • Samples:
    sentence1 sentence2
    what height should a floating vanity be If the piece measures 20 inches high and you want a height of 31 inches, you must mount it 11 inches above the floor. If you want the look of a floating sink with the entire vanity raised 12 inches or higher above the floor, you want a vanity of a smaller height.
    Owner Steve Hayes has been actively trying to sell the club since October and four parties were interested back in February.
    But in a statement the High Wycombe-based outfit said they were seeking fresh interest following stalled talks.
    Hayes announced his desire to sell up after Wycombe District Council decided not to back plans for a new stadium.
    Wasps chairman Mark Rigby added: "London Wasps has a long and successful history and is one of the best known brands in the game, and the board is convinced that the right backer exists.
    "With a great squad in place and the excellent Dai Young at the helm, we believe we are set to make a strong impact next season.
    "Time is however short and we urgently need a new investor or consortium to back this belief."
    The statement said the board, after independent advice, could confirm that London Wasps Holdings Limited remained a going concern.
    Wasps are enduring a torrid domestic season. They have won just two of their last 12 Premiership fixtures and sit second from bottom in the table.
    In addition Hayes, who also owns League One football club Wycombe Wanderers, is currently
    The 50-year-old businessman was one of two men arrested in February as part of Operation Tuleta, the investigation running alongside Operation Weeting, which was set up to probe alleged law-breaking at News International.
    He is currently on bail until June, subject to further enquiries.
    An 'imminent takeover' of London Wasps has fallen through, the Premiership strugglers have confirmed.
    can apple cider vinegar cure urinary infection? The takeaway Apple cider vinegar may have many health benefits, but it's not a cure for UTIs. If you have a UTI, make an appointment with your doctor. A short course of medication should relieve your symptoms within a few days.
  • Loss: CachedGISTEmbedLoss with these parameters:
    {'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': 0.025}
    

Training Hyperparameters

Non-Default Hyperparameters

  • eval_strategy: steps
  • per_device_train_batch_size: 64
  • per_device_eval_batch_size: 128
  • learning_rate: 2e-05
  • weight_decay: 0.001
  • num_train_epochs: 2
  • lr_scheduler_type: cosine_with_min_lr
  • lr_scheduler_kwargs: {'num_cycles': 0.5, 'min_lr': 5e-06}
  • warmup_ratio: 0.3
  • save_safetensors: False
  • fp16: True
  • push_to_hub: True
  • hub_model_id: bobox/DeBERTa2-0.9B-ST-v1-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: 64
  • per_device_eval_batch_size: 128
  • per_gpu_train_batch_size: None
  • per_gpu_eval_batch_size: None
  • gradient_accumulation_steps: 1
  • eval_accumulation_steps: None
  • learning_rate: 2e-05
  • weight_decay: 0.001
  • 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': 5e-06}
  • warmup_ratio: 0.3
  • 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/DeBERTa2-0.9B-ST-v1-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
  • batch_sampler: no_duplicates
  • multi_dataset_batch_sampler: proportional

Training Logs

Click to expand
Epoch Step Training Loss sciq pairs loss trivia pairs loss msmarco pairs loss scitail-pairs-qa loss openbookqa pairs loss nq pairs loss global dataset loss vitaminc-pairs loss scitail-pairs-pos loss gooaq pairs loss paws-pos loss qasc pairs loss xsum-pairs loss negation-triplets loss Qnli-dev_max_ap allNLI-dev_max_ap sts-test_spearman_cosine
0.0102 16 7.1882 - - - - - - - - - - - - - - - - -
0.0205 32 9.1489 - - - - - - - - - - - - - - - - -
0.0307 48 8.805 - - - - - - - - - - - - - - - - -
0.0409 64 5.7489 - - - - - - - - - - - - - - - - -
0.0512 80 4.7163 - - - - - - - - - - - - - - - - -
0.0614 96 3.176 - - - - - - - - - - - - - - - - -
0.0716 112 2.034 - - - - - - - - - - - - - - - - -
0.0818 128 1.1278 - - - - - - - - - - - - - - - - -
0.0921 144 0.7996 - - - - - - - - - - - - - - - - -
0.1004 157 - 0.1090 0.4664 0.7974 0.1105 0.7853 1.1498 0.4867 3.8214 0.0780 0.7758 0.0375 0.8442 0.1444 1.2527 0.6672 0.5230 0.8776
0.1023 160 0.54 - - - - - - - - - - - - - - - - -
0.1125 176 0.6267 - - - - - - - - - - - - - - - - -
0.1228 192 0.401 - - - - - - - - - - - - - - - - -
0.1330 208 0.455 - - - - - - - - - - - - - - - - -
0.1432 224 0.308 - - - - - - - - - - - - - - - - -
0.1535 240 0.2808 - - - - - - - - - - - - - - - - -
0.1637 256 0.319 - - - - - - - - - - - - - - - - -
0.1739 272 0.3241 - - - - - - - - - - - - - - - - -
0.1841 288 0.2181 - - - - - - - - - - - - - - - - -
0.1944 304 0.3247 - - - - - - - - - - - - - - - - -
0.2008 314 - 0.0483 0.1067 0.1743 0.0014 0.4045 0.1814 0.2370 3.3627 0.0271 0.2038 0.0234 0.1129 0.0382 0.7010 0.7243 0.5918 0.9171
0.2046 320 0.233 - - - - - - - - - - - - - - - - -
0.2148 336 0.1946 - - - - - - - - - - - - - - - - -
0.2251 352 0.2393 - - - - - - - - - - - - - - - - -
0.2353 368 0.1476 - - - - - - - - - - - - - - - - -
0.2455 384 0.1976 - - - - - - - - - - - - - - - - -
0.2558 400 0.1139 - - - - - - - - - - - - - - - - -
0.2660 416 0.1986 - - - - - - - - - - - - - - - - -
0.2762 432 0.2405 - - - - - - - - - - - - - - - - -
0.2864 448 0.1519 - - - - - - - - - - - - - - - - -
0.2967 464 0.1508 - - - - - - - - - - - - - - - - -
0.3012 471 - 0.0414 0.0961 0.0865 0.0004 0.3847 0.1033 0.1735 2.4167 0.0062 0.1280 0.0252 0.0391 0.0329 0.6828 0.7293 0.6023 0.9200
0.3069 480 0.1457 - - - - - - - - - - - - - - - - -
0.3171 496 0.1086 - - - - - - - - - - - - - - - - -
0.3274 512 0.1412 - - - - - - - - - - - - - - - - -
0.3376 528 0.1538 - - - - - - - - - - - - - - - - -
0.3478 544 0.1013 - - - - - - - - - - - - - - - - -
0.3581 560 0.1007 - - - - - - - - - - - - - - - - -
0.3683 576 0.0853 - - - - - - - - - - - - - - - - -
0.3785 592 0.0696 - - - - - - - - - - - - - - - - -
0.3887 608 0.1468 - - - - - - - - - - - - - - - - -
0.3990 624 0.1314 - - - - - - - - - - - - - - - - -
0.4015 628 - 0.0295 0.0647 0.0976 0.0001 0.3722 0.0893 0.2361 3.2355 0.0099 0.1432 0.0264 0.0721 0.0172 0.6764 0.7428 0.6036 0.9153
0.4092 640 0.149 - - - - - - - - - - - - - - - - -
0.4194 656 0.1402 - - - - - - - - - - - - - - - - -
0.4297 672 0.1056 - - - - - - - - - - - - - - - - -
0.4399 688 0.0932 - - - - - - - - - - - - - - - - -
0.4501 704 0.0534 - - - - - - - - - - - - - - - - -
0.4604 720 0.2175 - - - - - - - - - - - - - - - - -
0.4706 736 0.1107 - - - - - - - - - - - - - - - - -
0.4808 752 0.2301 - - - - - - - - - - - - - - - - -
0.4910 768 0.2317 - - - - - - - - - - - - - - - - -
0.5013 784 0.1084 - - - - - - - - - - - - - - - - -
0.5019 785 - 0.0324 0.0932 0.1156 0.0001 0.4128 0.1071 0.2526 3.9009 0.0121 0.1237 0.0254 0.0729 0.0098 0.6337 0.7422 0.6029 0.9171
0.5115 800 0.0799 - - - - - - - - - - - - - - - - -
0.5217 816 0.1466 - - - - - - - - - - - - - - - - -
0.5320 832 0.1208 - - - - - - - - - - - - - - - - -
0.5422 848 0.1021 - - - - - - - - - - - - - - - - -
0.5524 864 0.1391 - - - - - - - - - - - - - - - - -
0.5627 880 0.185 - - - - - - - - - - - - - - - - -
0.5729 896 0.1108 - - - - - - - - - - - - - - - - -
0.5831 912 0.0926 - - - - - - - - - - - - - - - - -
0.5934 928 0.157 - - - - - - - - - - - - - - - - -
0.6023 942 - 0.0307 0.0858 0.0844 0.0025 0.3581 0.1235 0.1544 2.8148 0.0050 0.1563 0.0268 0.0460 0.0177 0.5489 0.7193 0.6065 0.9218
0.6036 944 0.126 - - - - - - - - - - - - - - - - -
0.6138 960 0.1416 - - - - - - - - - - - - - - - - -
0.6240 976 0.157 - - - - - - - - - - - - - - - - -
0.6343 992 0.076 - - - - - - - - - - - - - - - - -
0.6445 1008 0.0956 - - - - - - - - - - - - - - - - -
0.6547 1024 0.1297 - - - - - - - - - - - - - - - - -
0.6650 1040 0.1673 - - - - - - - - - - - - - - - - -
0.6752 1056 0.0801 - - - - - - - - - - - - - - - - -
0.6854 1072 0.1508 - - - - - - - - - - - - - - - - -
0.6957 1088 0.082 - - - - - - - - - - - - - - - - -
0.7027 1099 - 0.0361 0.0896 0.0879 0.0001 0.4053 0.0798 0.3097 4.5101 0.0260 0.1373 0.0255 0.0795 0.0101 0.6732 0.7434 0.5941 0.9084
0.7059 1104 0.112 - - - - - - - - - - - - - - - - -
0.7161 1120 0.0565 - - - - - - - - - - - - - - - - -
0.7263 1136 0.1297 - - - - - - - - - - - - - - - - -
0.7366 1152 0.1792 - - - - - - - - - - - - - - - - -
0.7468 1168 0.1376 - - - - - - - - - - - - - - - - -
0.7570 1184 0.1362 - - - - - - - - - - - - - - - - -
0.7673 1200 0.1589 - - - - - - - - - - - - - - - - -
0.7775 1216 0.0846 - - - - - - - - - - - - - - - - -
0.7877 1232 0.1241 - - - - - - - - - - - - - - - - -
0.7980 1248 0.1532 - - - - - - - - - - - - - - - - -
0.8031 1256 - 0.0304 0.0667 0.1060 0.0003 0.3666 0.1305 0.2140 3.1243 0.0114 0.2109 0.0277 0.0328 0.0213 0.5495 0.7479 0.5907 0.9194
0.8082 1264 0.0859 - - - - - - - - - - - - - - - - -
0.8184 1280 0.0872 - - - - - - - - - - - - - - - - -
0.8286 1296 0.0685 - - - - - - - - - - - - - - - - -
0.8389 1312 0.0729 - - - - - - - - - - - - - - - - -
0.8491 1328 0.0679 - - - - - - - - - - - - - - - - -
0.8593 1344 0.0752 - - - - - - - - - - - - - - - - -
0.8696 1360 0.1651 - - - - - - - - - - - - - - - - -
0.8798 1376 0.0975 - - - - - - - - - - - - - - - - -
0.8900 1392 0.166 - - - - - - - - - - - - - - - - -
0.9003 1408 0.079 - - - - - - - - - - - - - - - - -
0.9035 1413 - 0.0356 0.0784 0.0609 0.0003 0.4281 0.0720 0.2313 3.4939 0.0141 0.2300 0.0268 0.0522 0.0061 0.5946 0.7379 0.6052 0.9102
0.9105 1424 0.09 - - - - - - - - - - - - - - - - -
0.9207 1440 0.0777 - - - - - - - - - - - - - - - - -
0.9309 1456 0.1623 - - - - - - - - - - - - - - - - -
0.9412 1472 0.08 - - - - - - - - - - - - - - - - -
0.9514 1488 0.0628 - - - - - - - - - - - - - - - - -
0.9616 1504 0.1695 - - - - - - - - - - - - - - - - -
0.9719 1520 0.0715 - - - - - - - - - - - - - - - - -
0.9821 1536 0.1493 - - - - - - - - - - - - - - - - -
0.9923 1552 0.0431 - - - - - - - - - - - - - - - - -
1.0026 1568 0.0549 - - - - - - - - - - - - - - - - -
1.0038 1570 - 0.0429 0.0583 0.0681 0.0019 0.4316 0.1454 0.1614 2.8374 0.0053 0.0735 0.0250 0.0282 0.0120 0.5641 0.7139 0.6081 0.9289
1.0128 1584 0.102 - - - - - - - - - - - - - - - - -
1.0230 1600 0.0806 - - - - - - - - - - - - - - - - -
1.0332 1616 0.0643 - - - - - - - - - - - - - - - - -
1.0435 1632 0.2551 - - - - - - - - - - - - - - - - -
1.0537 1648 0.1509 - - - - - - - - - - - - - - - - -
1.0639 1664 0.0928 - - - - - - - - - - - - - - - - -
1.0742 1680 0.1388 - - - - - - - - - - - - - - - - -
1.0844 1696 1.2414 - - - - - - - - - - - - - - - - -
1.0946 1712 4.1558 - - - - - - - - - - - - - - - - -
1.1042 1727 - 0.0589 0.2021 9.6693 0.6669 3.1183 1.2794 1.6158 3.3692 0.0116 5.4553 0.0264 4.7383 0.0407 0.9119 0.7052 0.5709 0.9119
1.1049 1728 1.8742 - - - - - - - - - - - - - - - - -
1.1151 1744 1.7176 - - - - - - - - - - - - - - - - -
1.1253 1760 0.3091 - - - - - - - - - - - - - - - - -
1.1355 1776 0.3178 - - - - - - - - - - - - - - - - -
1.1458 1792 0.173 - - - - - - - - - - - - - - - - -
1.1560 1808 0.1028 - - - - - - - - - - - - - - - - -
1.1662 1824 0.1533 - - - - - - - - - - - - - - - - -
1.1765 1840 0.2395 - - - - - - - - - - - - - - - - -
1.1867 1856 0.2036 - - - - - - - - - - - - - - - - -
1.1969 1872 0.2104 - - - - - - - - - - - - - - - - -
1.2046 1884 - 0.0323 0.0504 0.0626 0.0001 0.3769 0.0541 0.1662 2.7120 0.0100 0.0981 0.0282 0.0162 0.0219 0.5891 0.7460 0.5991 0.9239
1.2072 1888 0.239 - - - - - - - - - - - - - - - - -
1.2174 1904 0.2029 - - - - - - - - - - - - - - - - -
1.2276 1920 0.1581 - - - - - - - - - - - - - - - - -
1.2379 1936 0.1683 - - - - - - - - - - - - - - - - -
1.2481 1952 0.1056 - - - - - - - - - - - - - - - - -
1.2583 1968 0.1002 - - - - - - - - - - - - - - - - -
1.2685 1984 0.1527 - - - - - - - - - - - - - - - - -
1.2788 2000 0.2542 - - - - - - - - - - - - - - - - -
1.2890 2016 0.1295 - - - - - - - - - - - - - - - - -
1.2992 2032 0.1565 - - - - - - - - - - - - - - - - -
1.3050 2041 - 0.0341 0.0451 0.0323 0.0000 0.3145 0.0382 0.1816 3.2006 0.0092 0.1221 0.0286 0.0184 0.0134 0.5541 0.7137 0.6016 0.9313
1.3095 2048 0.222 - - - - - - - - - - - - - - - - -
1.3197 2064 0.1467 - - - - - - - - - - - - - - - - -
1.3299 2080 0.1023 - - - - - - - - - - - - - - - - -
1.3402 2096 0.1005 - - - - - - - - - - - - - - - - -
1.3504 2112 0.0889 - - - - - - - - - - - - - - - - -
1.3606 2128 0.0584 - - - - - - - - - - - - - - - - -
1.3708 2144 0.0334 - - - - - - - - - - - - - - - - -
1.3811 2160 0.0607 - - - - - - - - - - - - - - - - -
1.3913 2176 0.0673 - - - - - - - - - - - - - - - - -
1.4015 2192 0.0867 - - - - - - - - - - - - - - - - -
1.4054 2198 - 0.0363 0.0434 0.0318 0.0000 0.3318 0.0612 0.1406 2.7844 0.0135 0.1100 0.0276 0.0192 0.0169 0.5277 0.7531 0.6159 0.9247
1.4118 2208 0.0564 - - - - - - - - - - - - - - - - -
1.4220 2224 0.0778 - - - - - - - - - - - - - - - - -
1.4322 2240 0.0488 - - - - - - - - - - - - - - - - -
1.4425 2256 0.0418 - - - - - - - - - - - - - - - - -
1.4527 2272 0.0279 - - - - - - - - - - - - - - - - -
1.4629 2288 0.0929 - - - - - - - - - - - - - - - - -
1.4731 2304 0.0791 - - - - - - - - - - - - - - - - -
1.4834 2320 0.1057 - - - - - - - - - - - - - - - - -
1.4936 2336 0.0842 - - - - - - - - - - - - - - - - -
1.5038 2352 0.0622 - - - - - - - - - - - - - - - - -
1.5058 2355 - 0.0511 0.0411 0.0304 0.0000 0.3331 0.0650 0.2273 3.6822 0.0077 0.1491 0.0266 0.0848 0.0026 0.5201 0.7272 0.6080 0.9257

Framework Versions

  • Python: 3.10.12
  • Sentence Transformers: 3.0.1
  • Transformers: 4.42.4
  • PyTorch: 2.4.0+cu121
  • Accelerate: 0.32.1
  • Datasets: 2.21.0
  • Tokenizers: 0.19.1

Citation

BibTeX

Sentence Transformers

@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",
}