readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  model-index:
  - name: bert-large-cased-finetuned-prompt-20
    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-finetuned-prompt-20
  
  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: 0.7142
  
  ## 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: 64
  - eval_batch_size: 64
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 20.0
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss |
  |:-------------:|:-----:|:----:|:---------------:|
  | 1.3173        | 1.0   | 280  | 1.1293          |
  | 1.087         | 2.0   | 560  | 0.9716          |
  | 1.0064        | 3.0   | 840  | 0.9606          |
  | 0.9341        | 4.0   | 1120 | 0.8887          |
  | 0.8881        | 5.0   | 1400 | 0.8654          |
  | 0.8662        | 6.0   | 1680 | 0.8181          |
  | 0.8331        | 7.0   | 1960 | 0.8286          |
  | 0.8206        | 8.0   | 2240 | 0.7941          |
  | 0.8017        | 9.0   | 2520 | 0.7677          |
  | 0.772         | 10.0  | 2800 | 0.7711          |
  | 0.76          | 11.0  | 3080 | 0.7314          |
  | 0.7436        | 12.0  | 3360 | 0.7479          |
  | 0.7305        | 13.0  | 3640 | 0.7354          |
  | 0.7204        | 14.0  | 3920 | 0.7143          |
  | 0.7102        | 15.0  | 4200 | 0.7366          |
  | 0.7034        | 16.0  | 4480 | 0.7036          |
  | 0.6937        | 17.0  | 4760 | 0.7049          |
  | 0.695         | 18.0  | 5040 | 0.7080          |
  | 0.6923        | 19.0  | 5320 | 0.7110          |
  | 0.6886        | 20.0  | 5600 | 0.6969          |
  
  
  ### Framework versions
  
  - Transformers 4.26.0
  - Pytorch 1.13.1+cu116
  - Datasets 2.9.0
  - Tokenizers 0.13.2
  