readme: ---
  language:
  - en
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - glue
  metrics:
  - accuracy
  model-index:
  - name: bert-base-uncased-rte
    results:
    - task:
        type: text-classification
        name: Text Classification
      dataset:
        name: GLUE RTE
        type: glue
        args: rte
      metrics:
      - type: accuracy
        value: 0.6895306859205776
        name: Accuracy
    - task:
        type: natural-language-inference
        name: Natural Language Inference
      dataset:
        name: glue
        type: glue
        config: rte
        split: validation
      metrics:
      - type: accuracy
        value: 0.6823104693140795
        name: Accuracy
        verified: true
        verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiYTc4OTUzYmQ0NWRkMjdmYjI3ZDhmNWU5MTQ1YTM4ZTQzOWM5MTJjYzlmMjM3ZTE2Y2ZhMGJlNTI0OTJhYjNmMCIsInZlcnNpb24iOjF9.siPkmQhZKOZ1k_SyS1xIMavpK_CQ8tHTm39McCIEjiF7G1x62lbuKfrZsLoKoPf9XpNJqXoaXIRPCpHBKlfwCA
      - type: precision
        value: 0.7047619047619048
        name: Precision
        verified: true
        verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiMzdmMjk0ZjRkNzM4ZWE1ZGUyOWUxZTFjNmEyNTRmNjZmMDUxOTJlZmUxNjUzMWFhZTYzZTM1ZGNkMDg1YTMzYyIsInZlcnNpb24iOjF9.Cm2kMSTsWVPU9mBv8xAyvo7msTHdG3SECIYZ4kQ5RpN4NV3WE1k0EqmcGzAedwYNfSEg1qXL-qWDKOeoXDAnCw
      - type: recall
        value: 0.5648854961832062
        name: Recall
        verified: true
        verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiMjc1NTMzYWI5OGRjODdhYmJjZDQ3ODdiMWE3ODYzZjNhZDg1MGIyNjA1YzQwNzcwYTQzNjJkNGVjNmNjMWJmNSIsInZlcnNpb24iOjF9.MwRAu1AKhCt__2vBjhvEqU0gvXaJ5EMOOotKmwGXsuF3eGJEEDDuiWBgu9y291aqndTTwWvuH9CNQjGKLCoNCw
      - type: auc
        value: 0.7394646031580048
        name: AUC
        verified: true
        verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiOGQwMWVhZjlhNjhhZDRhNGYwNWUyOTZjMTgwMDQ5ZWM3MDcxNDc5OGJiNDE5NTNhOTU0MDMwYTdkYjcxNzFiZiIsInZlcnNpb24iOjF9.ZLyE_ZDWyVAr_GL_3lSqBmuIip7C13oj5kT1lI9JQOidt-IXsRHYUmJt_f7HWUNU1-FBD5lzHYcstF6WQ0VrAw
      - type: f1
        value: 0.6271186440677967
        name: F1
        verified: true
        verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiYmU0YjI4Y2MyMzU5ZTYzMmE0YzhjOTgwM2UwYTNhZDFmZWE3NTdhODMzYmU1ZWUxYTc2Yjk3Nzg3MjAyOThiOSIsInZlcnNpb24iOjF9.GJhnKNSHN5Sv9W3gl8fgPAAbM5EtMlhOHoOFcj_O65FLtcTi_ANpyv7gi41fPbMjS2TG4fgdVHQ_UZg7M6W2Cw
      - type: loss
        value: 0.7001310586929321
        name: loss
        verified: true
        verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiZjMwMTY5OGVkMzVhMzdjMmY1YmIzYTViOTRlNzcxMTI4NWNiOTQ5ZjMwMjRlODE4ZWUwMGVhZjhiMmIzM2ViOSIsInZlcnNpb24iOjF9.IsJhfeeqnVZFn10sOkCW7vAzfw1WQMwR8b99B3-hct_lrI1xodt5ySGltDvx2Q8ufD6hzfQ7YaDeHytDmeeFBw
  ---
  
  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
  should probably proofread and complete it, then remove this comment. -->
  
  # bert-base-uncased-rte
  
  This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the GLUE RTE dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.6972
  - Accuracy: 0.6895
  
  ## Model description
  
  More information needed
  
  ## Intended uses & limitations
  
  More information needed
  
  ## Training and evaluation data
  
  More information needed
  
  ## Training procedure
  
  ### Training hyperparameters
  
  The following hyperparameters were used during training:
  - learning_rate: 2e-05
  - train_batch_size: 16
  - eval_batch_size: 8
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 3.0
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
  | No log        | 1.0   | 156  | 0.6537          | 0.6318   |
  | No log        | 2.0   | 312  | 0.6383          | 0.6534   |
  | No log        | 3.0   | 468  | 0.6972          | 0.6895   |
  
  
  ### Framework versions
  
  - Transformers 4.20.0.dev0
  - Pytorch 1.11.0+cu113
  - Datasets 2.1.0
  - Tokenizers 0.12.1
  