readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  - f1
  model-index:
  - name: bert-base-uncased-ft-imdb
    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-base-uncased-ft-imdb
  
  This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the [steciuk/imdb](https://huggingface.co/datasets/steciuk/imdb) dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.2556
  - Accuracy: 0.945
  - F1: 0.9441
  
  and flowing results on the testing set:
  - Accuracy: 0.9417
  - F1: 0.9431
  
  ## 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     |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
  | 0.2943        | 0.38  | 750  | 0.1877          | 0.9257   | 0.9226 |
  | 0.2133        | 0.75  | 1500 | 0.1806          | 0.9375   | 0.9347 |
  | 0.1811        | 1.12  | 2250 | 0.1783          | 0.9443   | 0.9434 |
  | 0.1274        | 1.5   | 3000 | 0.2072          | 0.942    | 0.9400 |
  | 0.1177        | 1.88  | 3750 | 0.2737          | 0.9325   | 0.9336 |
  | 0.0817        | 2.25  | 4500 | 0.2706          | 0.9435   | 0.9420 |
  | 0.0644        | 2.62  | 5250 | 0.2630          | 0.9447   | 0.9434 |
  | 0.0604        | 3.0   | 6000 | 0.2556          | 0.945    | 0.9441 |
  
  
  ### Framework versions
  
  - Transformers 4.25.1
  - Pytorch 1.13.0+cu116
  - Datasets 2.7.1
  - Tokenizers 0.13.2
  