readme: ---
  tags:
  - generated_from_trainer
  model-index:
  - name: roberta-base-roberta-base-TF-weight1-epoch15
    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-roberta-base-TF-weight1-epoch15
  
  This model is a fine-tuned version of [](https://huggingface.co/) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 4.8322
  - Cls loss: 0.6900
  - Lm loss: 4.1423
  - Cls Accuracy: 0.5401
  - Cls F1: 0.3788
  - Cls Precision: 0.2917
  - Cls Recall: 0.5401
  - Perplexity: 62.95
  
  ## 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: 2
  - eval_batch_size: 2
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 15
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Cls loss | Lm loss | Cls Accuracy | Cls F1 | Cls Precision | Cls Recall | Perplexity |
  |:-------------:|:-----:|:-----:|:---------------:|:--------:|:-------:|:------------:|:------:|:-------------:|:----------:|:----------:|
  | 5.3158        | 1.0   | 3470  | 4.9858          | 0.6910   | 4.2949  | 0.5401       | 0.3788 | 0.2917        | 0.5401     | 73.32      |
  | 4.9772        | 2.0   | 6940  | 4.8876          | 0.6956   | 4.1920  | 0.4599       | 0.2898 | 0.2115        | 0.4599     | 66.15      |
  | 4.8404        | 3.0   | 10410 | 4.8454          | 0.6901   | 4.1553  | 0.5401       | 0.3788 | 0.2917        | 0.5401     | 63.77      |
  | 4.7439        | 4.0   | 13880 | 4.8177          | 0.6904   | 4.1274  | 0.5401       | 0.3788 | 0.2917        | 0.5401     | 62.02      |
  | 4.6667        | 5.0   | 17350 | 4.8065          | 0.6903   | 4.1163  | 0.5401       | 0.3788 | 0.2917        | 0.5401     | 61.33      |
  | 4.6018        | 6.0   | 20820 | 4.8081          | 0.6963   | 4.1119  | 0.5401       | 0.3788 | 0.2917        | 0.5401     | 61.06      |
  | 4.5447        | 7.0   | 24290 | 4.8089          | 0.6912   | 4.1177  | 0.5401       | 0.3788 | 0.2917        | 0.5401     | 61.42      |
  | 4.4944        | 8.0   | 27760 | 4.8128          | 0.6900   | 4.1228  | 0.5401       | 0.3788 | 0.2917        | 0.5401     | 61.73      |
  | 4.4505        | 9.0   | 31230 | 4.8152          | 0.6905   | 4.1248  | 0.5401       | 0.3788 | 0.2917        | 0.5401     | 61.85      |
  | 4.4116        | 10.0  | 34700 | 4.8129          | 0.6908   | 4.1221  | 0.5401       | 0.3788 | 0.2917        | 0.5401     | 61.69      |
  | 4.3787        | 11.0  | 38170 | 4.8146          | 0.6906   | 4.1241  | 0.5401       | 0.3788 | 0.2917        | 0.5401     | 61.81      |
  | 4.3494        | 12.0  | 41640 | 4.8229          | 0.6900   | 4.1329  | 0.5401       | 0.3788 | 0.2917        | 0.5401     | 62.36      |
  | 4.3253        | 13.0  | 45110 | 4.8287          | 0.6900   | 4.1388  | 0.5401       | 0.3788 | 0.2917        | 0.5401     | 62.73      |
  | 4.3075        | 14.0  | 48580 | 4.8247          | 0.6900   | 4.1347  | 0.5401       | 0.3788 | 0.2917        | 0.5401     | 62.47      |
  | 4.2936        | 15.0  | 52050 | 4.8322          | 0.6900   | 4.1423  | 0.5401       | 0.3788 | 0.2917        | 0.5401     | 62.95      |
  
  
  ### Framework versions
  
  - Transformers 4.21.2
  - Pytorch 1.12.1
  - Datasets 2.4.0
  - Tokenizers 0.12.1