readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  model-index:
  - name: bert-large-cased-sigir-LR100-0-prepend-40
    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. -->
  
  # bert-large-cased-sigir-LR100-0-prepend-40
  
  This model is a fine-tuned version of [bert-large-cased](https://huggingface.co/bert-large-cased) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 1.1764
  
  ## 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: 4e-05
  - train_batch_size: 30
  - eval_batch_size: 30
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 40.0
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss |
  |:-------------:|:-----:|:----:|:---------------:|
  | 2.6453        | 1.0   | 3    | 2.0522          |
  | 2.0488        | 2.0   | 6    | 1.7600          |
  | 1.9917        | 3.0   | 9    | 2.3036          |
  | 1.6084        | 4.0   | 12   | 1.4050          |
  | 1.856         | 5.0   | 15   | 1.3598          |
  | 1.6471        | 6.0   | 18   | 1.5274          |
  | 1.2358        | 7.0   | 21   | 1.6642          |
  | 1.4355        | 8.0   | 24   | 1.6109          |
  | 1.5753        | 9.0   | 27   | 1.8690          |
  | 1.5374        | 10.0  | 30   | 1.7986          |
  | 1.5063        | 11.0  | 33   | 1.4979          |
  | 1.2185        | 12.0  | 36   | 0.7390          |
  | 1.6042        | 13.0  | 39   | 1.1280          |
  | 1.1938        | 14.0  | 42   | 1.1252          |
  | 1.3215        | 15.0  | 45   | 1.6827          |
  | 1.0789        | 16.0  | 48   | 1.6349          |
  | 1.095         | 17.0  | 51   | 2.6303          |
  | 1.0088        | 18.0  | 54   | 0.9429          |
  | 1.015         | 19.0  | 57   | 1.4165          |
  | 1.2432        | 20.0  | 60   | 2.1061          |
  | 1.3365        | 21.0  | 63   | 1.5785          |
  | 1.2704        | 22.0  | 66   | 2.1850          |
  | 0.972         | 23.0  | 69   | 1.7769          |
  | 0.9052        | 24.0  | 72   | 1.5376          |
  | 0.976         | 25.0  | 75   | 2.1072          |
  | 1.1134        | 26.0  | 78   | 2.4425          |
  | 0.8328        | 27.0  | 81   | 1.5937          |
  | 1.1662        | 28.0  | 84   | 1.3542          |
  | 0.8575        | 29.0  | 87   | 1.2236          |
  | 0.728         | 30.0  | 90   | 1.2229          |
  | 1.1601        | 31.0  | 93   | 2.3723          |
  | 0.9426        | 32.0  | 96   | 1.6974          |
  | 0.8246        | 33.0  | 99   | 1.6610          |
  | 0.9777        | 34.0  | 102  | 1.1179          |
  | 0.7588        | 35.0  | 105  | 1.8809          |
  | 0.6929        | 36.0  | 108  | 1.9128          |
  | 0.6794        | 37.0  | 111  | 1.2689          |
  | 0.811         | 38.0  | 114  | 1.6715          |
  | 0.6805        | 39.0  | 117  | 2.0424          |
  | 0.9157        | 40.0  | 120  | 1.4210          |
  
  
  ### Framework versions
  
  - Transformers 4.26.0
  - Pytorch 1.13.1+cu116
  - Datasets 2.9.0
  - Tokenizers 0.13.2
  