readme: ---
  tags:
  - generated_from_trainer
  model-index:
  - name: gpt2-gpt2-TF-weight1-epoch5-with-eval
    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. -->
  
  # gpt2-gpt2-TF-weight1-epoch5-with-eval
  
  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: 4.9349
  - Cls loss: 0.9747
  - Lm loss: 3.9596
  - Cls Accuracy: 0.8340
  - Cls F1: 0.8334
  - Cls Precision: 0.8346
  - Cls Recall: 0.8340
  - Perplexity: 52.44
  
  ## 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 |
  |:-------------:|:-----:|:-----:|:---------------:|:--------:|:-------:|:------------:|:------:|:-------------:|:----------:|:----------:|
  | 4.8702        | 1.0   | 3470  | 4.7157          | 0.6951   | 4.0201  | 0.7752       | 0.7670 | 0.7978        | 0.7752     | 55.71      |
  | 4.5856        | 2.0   | 6940  | 4.6669          | 0.6797   | 3.9868  | 0.8352       | 0.8333 | 0.8406        | 0.8352     | 53.88      |
  | 4.4147        | 3.0   | 10410 | 4.6619          | 0.6899   | 3.9716  | 0.8375       | 0.8368 | 0.8384        | 0.8375     | 53.07      |
  | 4.2479        | 4.0   | 13880 | 4.8305          | 0.8678   | 3.9622  | 0.8403       | 0.8396 | 0.8413        | 0.8403     | 52.57      |
  | 4.1281        | 5.0   | 17350 | 4.9349          | 0.9747   | 3.9596  | 0.8340       | 0.8334 | 0.8346        | 0.8340     | 52.44      |
  
  
  ### Framework versions
  
  - Transformers 4.21.2
  - Pytorch 1.12.1
  - Datasets 2.4.0
  - Tokenizers 0.12.1