readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  - f1
  model-index:
  - name: bert-nlp-project-ft-imdb-ds-google
    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. -->
  
  # bert-nlp-project-ft-imdb-ds-google
  
  This model is a fine-tuned version of [jestemleon/bert-nlp-project-imdb](https://huggingface.co/jestemleon/bert-nlp-project-imdb) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.3097
  - Accuracy: 0.9124
  - F1: 0.9197
  
  ## 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: 16
  - eval_batch_size: 16
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 3
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
  | 0.3517        | 0.37  | 196  | 0.2556          | 0.9105   | 0.9187 |
  | 0.27          | 0.75  | 392  | 0.2369          | 0.9038   | 0.9105 |
  | 0.2246        | 1.12  | 588  | 0.2630          | 0.9133   | 0.9205 |
  | 0.1869        | 1.49  | 784  | 0.2885          | 0.9038   | 0.9071 |
  | 0.1696        | 1.86  | 980  | 0.2811          | 0.9152   | 0.9233 |
  | 0.1474        | 2.24  | 1176 | 0.2918          | 0.9190   | 0.9243 |
  | 0.1187        | 2.61  | 1372 | 0.3045          | 0.9133   | 0.9212 |
  | 0.1077        | 2.98  | 1568 | 0.3097          | 0.9124   | 0.9197 |
  
  
  ### Framework versions
  
  - Transformers 4.25.1
  - Pytorch 1.13.0+cu116
  - Datasets 2.8.0
  - Tokenizers 0.13.2
  