readme: ---
  tags:
  - generated_from_trainer
  model-index:
  - name: roberta-base-roberta-base-TF-weight2-epoch5
    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-weight2-epoch5
  
  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: 5.5174
  - Cls loss: 0.6899
  - Lm loss: 4.1376
  - Cls Accuracy: 0.5401
  - Cls F1: 0.3788
  - Cls Precision: 0.2917
  - Cls Recall: 0.5401
  - Perplexity: 62.65
  
  ## 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: 5
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Cls loss | Lm loss | Cls Accuracy | Cls F1 | Cls Precision | Cls Recall | Perplexity |
  |:-------------:|:-----:|:-----:|:---------------:|:--------:|:-------:|:------------:|:------:|:-------------:|:----------:|:----------:|
  | 6.023         | 1.0   | 3470  | 5.6863          | 0.6910   | 4.3046  | 0.5401       | 0.3788 | 0.2917        | 0.5401     | 74.04      |
  | 5.6871        | 2.0   | 6940  | 5.5897          | 0.6926   | 4.2045  | 0.5401       | 0.3788 | 0.2917        | 0.5401     | 66.99      |
  | 5.5587        | 3.0   | 10410 | 5.5414          | 0.6905   | 4.1604  | 0.5401       | 0.3788 | 0.2917        | 0.5401     | 64.10      |
  | 5.481         | 4.0   | 13880 | 5.5208          | 0.6900   | 4.1409  | 0.5401       | 0.3788 | 0.2917        | 0.5401     | 62.86      |
  | 5.4338        | 5.0   | 17350 | 5.5174          | 0.6899   | 4.1376  | 0.5401       | 0.3788 | 0.2917        | 0.5401     | 62.65      |
  
  
  ### Framework versions
  
  - Transformers 4.21.2
  - Pytorch 1.12.1
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  