readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - massive
  metrics:
  - accuracy
  model-index:
  - name: distilroberta-base-Massive-intent
    results:
    - task:
        name: Text Classification
        type: text-classification
      dataset:
        name: massive
        type: massive
        config: en-US
        split: train
        args: en-US
      metrics:
      - name: Accuracy
        type: accuracy
        value: 0.8937530742744713
  ---
  
  <!-- 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-base-Massive-intent
  
  This model is a fine-tuned version of [distilroberta-base](https://huggingface.co/distilroberta-base) on the massive dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.6618
  - Accuracy: 0.8938
  
  ## 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 |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
  | 1.41          | 1.0   | 720  | 0.6742          | 0.8288   |
  | 0.4978        | 2.0   | 1440 | 0.5150          | 0.8751   |
  | 0.3009        | 3.0   | 2160 | 0.5705          | 0.8790   |
  | 0.1953        | 4.0   | 2880 | 0.5887          | 0.8795   |
  | 0.127         | 5.0   | 3600 | 0.6123          | 0.8810   |
  | 0.0914        | 6.0   | 4320 | 0.6575          | 0.8834   |
  | 0.0583        | 7.0   | 5040 | 0.6618          | 0.8938   |
  | 0.0355        | 8.0   | 5760 | 0.7591          | 0.8864   |
  | 0.0259        | 9.0   | 6480 | 0.8087          | 0.8780   |
  | 0.02          | 10.0  | 7200 | 0.7964          | 0.8888   |
  
  
  ### Framework versions
  
  - Transformers 4.22.1
  - Pytorch 1.12.1+cu113
  - Datasets 2.5.1
  - Tokenizers 0.12.1
  