readme: ---
  language:
  - en
  license: mit
  tags:
  - generated_from_trainer
  datasets:
  - glue
  metrics:
  - accuracy
  model-index:
  - name: roberta-base-rte
    results:
    - task:
        type: text-classification
        name: Text Classification
      dataset:
        name: GLUE RTE
        type: glue
        args: rte
      metrics:
      - type: accuracy
        value: 0.7978339350180506
        name: Accuracy
    - task:
        type: natural-language-inference
        name: Natural Language Inference
      dataset:
        name: glue
        type: glue
        config: rte
        split: validation
      metrics:
      - type: accuracy
        value: 0.7906137184115524
        name: Accuracy
        verified: true
        verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiMWVhOWZkNGYyMWRmNzdmZTM5MTVmNzFhNjVlMzA1NWU4YjJjODk5ZjM4MTY1Yjg0MTc0MmRmZTNkMzIwZDAzNyIsInZlcnNpb24iOjF9.nFZpFXDSLEIcO-_Z43_5b08GIVQiU9hFUEZpTftW3h6_zqIYZSuM7jOIuDYS3YYWMz42NoH_kosEpJg7TK15Bg
      - type: precision
        value: 0.7552447552447552
        name: Precision
        verified: true
        verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiNDYxZTkzZjk1NDU0MjhmNzYxM2IzNzJjNjE1Y2UxYTQ0MTJmNjJlMmUzNGY3MDdiMDAyZjQ2MmE4ODExYjYxNiIsInZlcnNpb24iOjF9.98rxE2rgU5ECIv4MGzMnaPRRYg3kGLsG4pZbMuYeAFEfXqBU1K0i_G-_cU7oxIqGypNmMhYVhVxZfC7wS_saAw
      - type: recall
        value: 0.8244274809160306
        name: Recall
        verified: true
        verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiNTNhNDZiZjMzOWM0ZGJkODMzM2VmOGYxMTYyZDNjYTgwN2NiMDFlOGI4NzM5NjQ5ODc4MWM2YmM5MTZjMWFiOCIsInZlcnNpb24iOjF9.C9aEgIz392h-zFSd98CSmzQ7Y6N0Xq3VmGIMEq9aP3dQPPrtUfl9Ms_QMSgSyWMPDYHup3SAGAP0JmkiVeOoBg
      - type: auc
        value: 0.8564258078008994
        name: AUC
        verified: true
        verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiNWVlNGVhOTRkNjUxMGMwZmE0YzBjZDQ0YzQ0ODRmYTc0YjI0MDQ2NTNkOWQ2YjU3MmI5NzI4ZWIwMzBlNTQ1NyIsInZlcnNpb24iOjF9.hSyJjOktSt3AItNnVtgWO9jgHwtNbhv4_KrWEV1r_ywopvbpNmSG4yzaI9PZ_bQQ-4ZSmFM8zUYxCl656TWoDQ
      - type: f1
        value: 0.7883211678832117
        name: F1
        verified: true
        verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiNGI4Mzk1MTkyZGJkZjQ1MWZkZDIyZTA3OTU0YmZhNjI4NGUxMjk4ZGZhNjZkN2JmZWRmZGU3OWM5Zjc0ODg4NyIsInZlcnNpb24iOjF9.gkQh5Y4dm8NimTtI0i-gHAYTxFRNlOtdgz-NJW8EvNKeFNWYXqa495Q-KEnSBRv88RKiNQXBp-3fyttjhX2HCw
      - type: loss
        value: 0.5560466051101685
        name: loss
        verified: true
        verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiZjczNTgxODRlN2Q4NmUyOTdjNzE0ZTZkOWVjZDgzNTdhODAyNGVkM2M1M2I4MGM2ZWMyMDE0ODdhMzQ0N2E1NCIsInZlcnNpb24iOjF9.TfXjqAGtiIQ62HzMkEQmKMMcL9a9bvfBTJARVmTPlIdOOxxF-xuVLXSyFqq2ajhDJXmUEETXBcFzSon_zbHTCQ
  ---
  
  <!-- 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. -->
  
  # roberta-base-rte
  
  This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the GLUE RTE dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.5446
  - Accuracy: 0.7978
  
  ## 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: 1e-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
  - lr_scheduler_warmup_ratio: 0.06
  - num_epochs: 10.0
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
  | No log        | 1.0   | 156  | 0.7023          | 0.4729   |
  | No log        | 2.0   | 312  | 0.6356          | 0.6895   |
  | No log        | 3.0   | 468  | 0.5177          | 0.7617   |
  | 0.6131        | 4.0   | 624  | 0.6238          | 0.7473   |
  | 0.6131        | 5.0   | 780  | 0.5446          | 0.7978   |
  | 0.6131        | 6.0   | 936  | 0.9697          | 0.7545   |
  | 0.2528        | 7.0   | 1092 | 1.1004          | 0.7690   |
  | 0.2528        | 8.0   | 1248 | 1.1937          | 0.7726   |
  | 0.2528        | 9.0   | 1404 | 1.3313          | 0.7726   |
  | 0.1073        | 10.0  | 1560 | 1.3534          | 0.7726   |
  
  
  ### Framework versions
  
  - Transformers 4.20.0.dev0
  - Pytorch 1.11.0+cu113
  - Datasets 2.1.0
  - Tokenizers 0.12.1
  