readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - f1
  - accuracy
  model-index:
  - name: Goodreads_Books_Reviews_BERT_50
    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. -->
  
  # Goodreads_Books_Reviews_BERT_50
  
  This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.9665
  - F1: 0.6343
  - Accuracy: 0.6343
  
  ## 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: 32
  - eval_batch_size: 32
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 500
  - num_epochs: 4
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | F1     | Accuracy |
  |:-------------:|:-----:|:-----:|:---------------:|:------:|:--------:|
  | 0.9881        | 1.0   | 4219  | 0.9548          | 0.6185 | 0.6183   |
  | 0.8735        | 2.0   | 8438  | 0.9506          | 0.6278 | 0.626    |
  | 0.7147        | 3.0   | 12657 | 0.9665          | 0.6343 | 0.6343   |
  | 0.6294        | 4.0   | 16876 | 1.0249          | 0.6341 | 0.6334   |
  
  
  ### Framework versions
  
  - Transformers 4.20.1
  - Pytorch 1.11.0
  - Datasets 2.1.0
  - Tokenizers 0.12.1
  