readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - imdb
  metrics:
  - accuracy
  - f1
  model-index:
  - name: finetuned-base_small
    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: 0.89416
      - name: F1
        type: f1
        value: 0.9441229885542932
  ---
  
  <!-- 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. -->
  
  # finetuned-base_small
  
  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: 0.3962
  - Accuracy: 0.8942
  - F1: 0.9441
  
  ## 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     |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
  | 0.3459        | 0.64  | 500  | 0.1283          | 0.9505   | 0.9746 |
  | 0.2389        | 1.28  | 1000 | 0.1054          | 0.9595   | 0.9793 |
  | 0.1927        | 1.92  | 1500 | 0.1447          | 0.9457   | 0.9721 |
  | 0.1408        | 2.56  | 2000 | 0.1261          | 0.9594   | 0.9793 |
  | 0.1168        | 3.2   | 2500 | 0.3962          | 0.8942   | 0.9441 |
  
  
  ### Framework versions
  
  - Transformers 4.25.1
  - Pytorch 1.12.1+cu113
  - Datasets 2.7.1
  - Tokenizers 0.13.2
  