readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - emotion
  model-index:
  - name: nlp_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. -->
  
  # nlp_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: 0.2791
  
  ## 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 |
  |:-------------:|:-----:|:----:|:---------------:|
  | 0.8887        | 0.25  | 500  | 0.4212          |
  | 0.3216        | 0.5   | 1000 | 0.3192          |
  | 0.2649        | 0.75  | 1500 | 0.2746          |
  | 0.2535        | 1.0   | 2000 | 0.2573          |
  | 0.163         | 1.25  | 2500 | 0.2157          |
  | 0.1868        | 1.5   | 3000 | 0.2118          |
  | 0.1258        | 1.75  | 3500 | 0.2319          |
  | 0.1726        | 2.0   | 4000 | 0.1853          |
  | 0.1035        | 2.25  | 4500 | 0.2146          |
  | 0.1135        | 2.5   | 5000 | 0.2207          |
  | 0.1117        | 2.75  | 5500 | 0.2496          |
  | 0.1145        | 3.0   | 6000 | 0.2482          |
  | 0.0726        | 3.25  | 6500 | 0.2654          |
  | 0.0828        | 3.5   | 7000 | 0.2622          |
  | 0.0817        | 3.75  | 7500 | 0.2775          |
  | 0.0689        | 4.0   | 8000 | 0.2791          |
  
  
  ### Framework versions
  
  - Transformers 4.15.0
  - Pytorch 1.12.0+cu113
  - Datasets 2.4.0
  - Tokenizers 0.10.3
  