readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - emotion
  metrics:
  - accuracy
  - f1
  model-index:
  - name: bert-tiny-mlm-finetuned-imdb-finetuned-emotion
    results:
    - task:
        name: Text Classification
        type: text-classification
      dataset:
        name: emotion
        type: emotion
        config: default
        split: train
        args: default
      metrics:
      - name: Accuracy
        type: accuracy
        value: 0.9065
      - name: F1
        type: f1
        value: 0.908345493577161
  ---
  
  <!-- 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-tiny-mlm-finetuned-imdb-finetuned-emotion
  
  This model is a fine-tuned version of [muhtasham/bert-tiny-mlm-finetuned-imdb](https://huggingface.co/muhtasham/bert-tiny-mlm-finetuned-imdb) on the emotion dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.2401
  - Accuracy: 0.9065
  - F1: 0.9083
  
  ## 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     |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
  | 1.4581        | 2.0   | 500  | 1.0158          | 0.672    | 0.6025 |
  | 0.8545        | 4.0   | 1000 | 0.6368          | 0.842    | 0.8344 |
  | 0.5846        | 6.0   | 1500 | 0.4626          | 0.877    | 0.8745 |
  | 0.422         | 8.0   | 2000 | 0.3520          | 0.8925   | 0.8917 |
  | 0.3222        | 10.0  | 2500 | 0.2934          | 0.9035   | 0.9039 |
  | 0.2695        | 12.0  | 3000 | 0.2573          | 0.9055   | 0.9056 |
  | 0.2247        | 14.0  | 3500 | 0.2396          | 0.9115   | 0.9122 |
  | 0.1986        | 16.0  | 4000 | 0.2311          | 0.9155   | 0.9154 |
  | 0.1773        | 18.0  | 4500 | 0.2261          | 0.9125   | 0.9136 |
  | 0.1554        | 20.0  | 5000 | 0.2309          | 0.914    | 0.9144 |
  | 0.1407        | 22.0  | 5500 | 0.2401          | 0.9065   | 0.9083 |
  
  
  ### Framework versions
  
  - Transformers 4.24.0
  - Pytorch 1.12.1+cu113
  - Datasets 2.7.1
  - Tokenizers 0.13.2
  