readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - imdb
  metrics:
  - accuracy
  - f1
  model-index:
  - name: small-vanilla-target-imdb
    results:
    - task:
        name: Text Classification
        type: text-classification
      dataset:
        name: imdb
        type: imdb
        config: plain_text
        split: train
        args: plain_text
      metrics:
      - name: Accuracy
        type: accuracy
        value: 0.81456
      - name: F1
        type: f1
        value: 0.8978044264174235
  ---
  
  <!-- 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. -->
  
  # small-vanilla-target-imdb
  
  This model is a fine-tuned version of [google/bert_uncased_L-4_H-512_A-8](https://huggingface.co/google/bert_uncased_L-4_H-512_A-8) on the imdb dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.7710
  - Accuracy: 0.8146
  - F1: 0.8978
  
  ## 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: 3e-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: constant
  - num_epochs: 200
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
  | 0.3417        | 0.64  | 500  | 0.1678          | 0.9286   | 0.9630 |
  | 0.2401        | 1.28  | 1000 | 0.1262          | 0.9525   | 0.9757 |
  | 0.1907        | 1.92  | 1500 | 0.2724          | 0.8963   | 0.9453 |
  | 0.1397        | 2.56  | 2000 | 0.2378          | 0.9247   | 0.9609 |
  | 0.11          | 3.2   | 2500 | 0.7710          | 0.8146   | 0.8978 |
  
  
  ### Framework versions
  
  - Transformers 4.25.1
  - Pytorch 1.12.1
  - Datasets 2.7.1
  - Tokenizers 0.13.2
  