readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - emotion
  model-index:
  - name: bert_emo_classifier
    results: []
  ---
  
  <!-- 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_emo_classifier
  
  This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the emotion dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.2652
  
  ## 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: 8
  - eval_batch_size: 8
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 4
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss |
  |:-------------:|:-----:|:----:|:---------------:|
  | 0.8874        | 0.25  | 500  | 0.4256          |
  | 0.3255        | 0.5   | 1000 | 0.3233          |
  | 0.2754        | 0.75  | 1500 | 0.2736          |
  | 0.242         | 1.0   | 2000 | 0.2263          |
  | 0.1661        | 1.25  | 2500 | 0.2118          |
  | 0.1614        | 1.5   | 3000 | 0.1812          |
  | 0.1434        | 1.75  | 3500 | 0.1924          |
  | 0.1629        | 2.0   | 4000 | 0.1766          |
  | 0.1066        | 2.25  | 4500 | 0.2100          |
  | 0.1313        | 2.5   | 5000 | 0.1996          |
  | 0.1113        | 2.75  | 5500 | 0.2185          |
  | 0.115         | 3.0   | 6000 | 0.2406          |
  | 0.0697        | 3.25  | 6500 | 0.2485          |
  | 0.0835        | 3.5   | 7000 | 0.2391          |
  | 0.0637        | 3.75  | 7500 | 0.2695          |
  | 0.0707        | 4.0   | 8000 | 0.2652          |
  
  
  ### Framework versions
  
  - Transformers 4.15.0
  - Pytorch 1.12.1+cu113
  - Datasets 2.4.0
  - Tokenizers 0.10.3
  