readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - emotion
  metrics:
  - accuracy
  model-index:
  - name: distilroberta-emotion-intent
    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: 0.9435
  ---
  
  <!-- 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. -->
  
  # distilroberta-emotion-intent
  
  This model is a fine-tuned version of [distilroberta-base](https://huggingface.co/distilroberta-base) on the emotion dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.1496
  - Accuracy: 0.9435
  
  ## 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: 5e-05
  - train_batch_size: 16
  - eval_batch_size: 16
  - seed: 33
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 15
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
  | 0.4501        | 1.0   | 1000 | 0.2432          | 0.924    |
  | 0.1947        | 2.0   | 2000 | 0.1646          | 0.934    |
  | 0.1497        | 3.0   | 3000 | 0.1382          | 0.9405   |
  | 0.1316        | 4.0   | 4000 | 0.1496          | 0.9435   |
  | 0.1145        | 5.0   | 5000 | 0.1684          | 0.9385   |
  | 0.1           | 6.0   | 6000 | 0.2342          | 0.943    |
  | 0.0828        | 7.0   | 7000 | 0.2807          | 0.939    |
  
  
  ### Framework versions
  
  - Transformers 4.22.1
  - Pytorch 1.12.1+cu113
  - Datasets 2.5.1
  - Tokenizers 0.12.1
  