readme: ---
  tags:
  - generated_from_trainer
  model-index:
  - name: roberta-base-roberta-base-TF-weight0.5-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-weight0.5-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: 4.4274
  - Cls loss: 0.5846
  - Lm loss: 4.1354
  - Cls Accuracy: 0.7533
  - Cls F1: 0.7495
  - Cls Precision: 0.7581
  - Cls Recall: 0.7533
  - Perplexity: 62.51
  
  ## 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 |
  |:-------------:|:-----:|:-----:|:---------------:|:--------:|:-------:|:------------:|:------:|:-------------:|:----------:|:----------:|
  | 4.9675        | 1.0   | 3470  | 4.6427          | 0.6907   | 4.2975  | 0.5401       | 0.3788 | 0.2917        | 0.5401     | 73.51      |
  | 4.6381        | 2.0   | 6940  | 4.5451          | 0.6935   | 4.1983  | 0.4599       | 0.2898 | 0.2115        | 0.4599     | 66.58      |
  | 4.5086        | 3.0   | 10410 | 4.5036          | 0.6902   | 4.1585  | 0.5401       | 0.3788 | 0.2917        | 0.5401     | 63.98      |
  | 4.4302        | 4.0   | 13880 | 4.4818          | 0.6877   | 4.1379  | 0.5447       | 0.3910 | 0.6764        | 0.5447     | 62.67      |
  | 4.3315        | 5.0   | 17350 | 4.4274          | 0.5846   | 4.1354  | 0.7533       | 0.7495 | 0.7581        | 0.7533     | 62.51      |
  
  
  ### Framework versions
  
  - Transformers 4.21.2
  - Pytorch 1.12.1
  - Datasets 2.4.0
  - Tokenizers 0.12.1