readme: ---
  license: mit
  tags:
  - generated_from_trainer
  model-index:
  - name: roberta-base-finetuned-squad
    results: []
  ---
  
  <!-- 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-finetuned-squad
  
  This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.0001
  
  ## 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: 1
  - eval_batch_size: 1
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 100
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss |
  |:-------------:|:-----:|:----:|:---------------:|
  | No log        | 1.0   | 2    | 5.6504          |
  | No log        | 2.0   | 4    | 5.0165          |
  | No log        | 3.0   | 6    | 4.2438          |
  | No log        | 4.0   | 8    | 3.2047          |
  | No log        | 5.0   | 10   | 2.3533          |
  | No log        | 6.0   | 12   | 2.1072          |
  | No log        | 7.0   | 14   | 1.4145          |
  | No log        | 8.0   | 16   | 1.0086          |
  | No log        | 9.0   | 18   | 0.5869          |
  | No log        | 10.0  | 20   | 0.2890          |
  | No log        | 11.0  | 22   | 0.1551          |
  | No log        | 12.0  | 24   | 0.0902          |
  | No log        | 13.0  | 26   | 0.0503          |
  | No log        | 14.0  | 28   | 0.0312          |
  | No log        | 15.0  | 30   | 0.0173          |
  | No log        | 16.0  | 32   | 0.0113          |
  | No log        | 17.0  | 34   | 0.0085          |
  | No log        | 18.0  | 36   | 0.0056          |
  | No log        | 19.0  | 38   | 0.0035          |
  | No log        | 20.0  | 40   | 0.0024          |
  | No log        | 21.0  | 42   | 0.0018          |
  | No log        | 22.0  | 44   | 0.0012          |
  | No log        | 23.0  | 46   | 0.0011          |
  | No log        | 24.0  | 48   | 0.0009          |
  | No log        | 25.0  | 50   | 0.0007          |
  | No log        | 26.0  | 52   | 0.0006          |
  | No log        | 27.0  | 54   | 0.0006          |
  | No log        | 28.0  | 56   | 0.0005          |
  | No log        | 29.0  | 58   | 0.0004          |
  | No log        | 30.0  | 60   | 0.0004          |
  | No log        | 31.0  | 62   | 0.0004          |
  | No log        | 32.0  | 64   | 0.0004          |
  | No log        | 33.0  | 66   | 0.0004          |
  | No log        | 34.0  | 68   | 0.0003          |
  | No log        | 35.0  | 70   | 0.0003          |
  | No log        | 36.0  | 72   | 0.0003          |
  | No log        | 37.0  | 74   | 0.0003          |
  | No log        | 38.0  | 76   | 0.0002          |
  | No log        | 39.0  | 78   | 0.0002          |
  | No log        | 40.0  | 80   | 0.0002          |
  | No log        | 41.0  | 82   | 0.0002          |
  | No log        | 42.0  | 84   | 0.0002          |
  | No log        | 43.0  | 86   | 0.0002          |
  | No log        | 44.0  | 88   | 0.0002          |
  | No log        | 45.0  | 90   | 0.0002          |
  | No log        | 46.0  | 92   | 0.0002          |
  | No log        | 47.0  | 94   | 0.0002          |
  | No log        | 48.0  | 96   | 0.0002          |
  | No log        | 49.0  | 98   | 0.0002          |
  | No log        | 50.0  | 100  | 0.0002          |
  | No log        | 51.0  | 102  | 0.0002          |
  | No log        | 52.0  | 104  | 0.0002          |
  | No log        | 53.0  | 106  | 0.0002          |
  | No log        | 54.0  | 108  | 0.0002          |
  | No log        | 55.0  | 110  | 0.0002          |
  | No log        | 56.0  | 112  | 0.0002          |
  | No log        | 57.0  | 114  | 0.0002          |
  | No log        | 58.0  | 116  | 0.0002          |
  | No log        | 59.0  | 118  | 0.0002          |
  | No log        | 60.0  | 120  | 0.0002          |
  | No log        | 61.0  | 122  | 0.0001          |
  | No log        | 62.0  | 124  | 0.0001          |
  | No log        | 63.0  | 126  | 0.0001          |
  | No log        | 64.0  | 128  | 0.0001          |
  | No log        | 65.0  | 130  | 0.0001          |
  | No log        | 66.0  | 132  | 0.0001          |
  | No log        | 67.0  | 134  | 0.0001          |
  | No log        | 68.0  | 136  | 0.0001          |
  | No log        | 69.0  | 138  | 0.0001          |
  | No log        | 70.0  | 140  | 0.0001          |
  | No log        | 71.0  | 142  | 0.0001          |
  | No log        | 72.0  | 144  | 0.0001          |
  | No log        | 73.0  | 146  | 0.0001          |
  | No log        | 74.0  | 148  | 0.0001          |
  | No log        | 75.0  | 150  | 0.0001          |
  | No log        | 76.0  | 152  | 0.0001          |
  | No log        | 77.0  