readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - emotion
  metrics:
  - f1
  model-index:
  - name: bert-base-cased-finetuned-emotion
    results:
    - task:
        name: Text Classification
        type: text-classification
      dataset:
        name: emotion
        type: emotion
        args: default
      metrics:
      - name: F1
        type: f1
        value: 0.9365323747830425
  ---
  
  <!-- 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-cased-finetuned-emotion
  
  This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the emotion dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.1342
  - F1: 0.9365
  
  ## 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: 64
  - eval_batch_size: 64
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 5
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | F1     |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 0.7357        | 1.0   | 250  | 0.2318          | 0.9224 |
  | 0.1758        | 2.0   | 500  | 0.1679          | 0.9349 |
  | 0.1228        | 3.0   | 750  | 0.1385          | 0.9382 |
  | 0.0961        | 4.0   | 1000 | 0.1452          | 0.9340 |
  | 0.0805        | 5.0   | 1250 | 0.1342          | 0.9365 |
  
  
  ### Framework versions
  
  - Transformers 4.12.5
  - Pytorch 1.10.0+cu111
  - Datasets 1.16.1
  - Tokenizers 0.10.3
  