readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - imdb
  metrics:
  - accuracy
  - f1
  model-index:
  - name: bert_uncased_L-2_H-128_A-2-finetuned-emotion-finetuned-tweet
    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: 0.87168
      - name: F1
        type: f1
        value: 0.8716747437975058
  ---
  
  <!-- 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_uncased_L-2_H-128_A-2-finetuned-emotion-finetuned-tweet
  
  This model is a fine-tuned version of [muhtasham/bert_uncased_L-2_H-128_A-2-finetuned-emotion](https://huggingface.co/muhtasham/bert_uncased_L-2_H-128_A-2-finetuned-emotion) on the imdb dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.4004
  - Accuracy: 0.8717
  - F1: 0.8717
  
  ## 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: 64
  - eval_batch_size: 64
  - 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     |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
  | 0.4751        | 1.28  | 500  | 0.3880          | 0.828    | 0.8277 |
  | 0.3453        | 2.56  | 1000 | 0.3282          | 0.8608   | 0.8607 |
  | 0.2973        | 3.84  | 1500 | 0.3140          | 0.8695   | 0.8695 |
  | 0.26          | 5.12  | 2000 | 0.3154          | 0.8736   | 0.8735 |
  | 0.2218        | 6.39  | 2500 | 0.3144          | 0.8756   | 0.8756 |
  | 0.1977        | 7.67  | 3000 | 0.3197          | 0.876    | 0.8760 |
  | 0.1656        | 8.95  | 3500 | 0.3526          | 0.8737   | 0.8735 |
  | 0.1404        | 10.23 | 4000 | 0.3865          | 0.8691   | 0.8689 |
  | 0.121         | 11.51 | 4500 | 0.4004          | 0.8717   | 0.8717 |
  
  
  ### Framework versions
  
  - Transformers 4.24.0
  - Pytorch 1.12.1+cu113
  - Datasets 2.7.0
  - Tokenizers 0.13.2
  