readme: ---
  license: mit
  tags:
  - generated_from_trainer
  datasets:
  - amazon_reviews_multi
  metrics:
  - accuracy
  model-index:
  - name: output
    results:
    - task:
        name: Text Classification
        type: text-classification
      dataset:
        name: amazon_reviews_multi
        type: amazon_reviews_multi
        config: en
        split: train
        args: en
      metrics:
      - name: Accuracy
        type: accuracy
        value: 0.6182
  ---
  
  <!-- 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. -->
  
  # output
  
  This model is a fine-tuned version of [microsoft/deberta-v3-base](https://huggingface.co/microsoft/deberta-v3-base) on the amazon_reviews_multi dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.9114
  - Accuracy: 0.6182
  
  ## 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
  - lr_scheduler_warmup_steps: 200
  - num_epochs: 2
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Accuracy |
  |:-------------:|:-----:|:-----:|:---------------:|:--------:|
  | 0.9326        | 0.2   | 5000  | 0.9682          | 0.592    |
  | 0.9318        | 0.4   | 10000 | 0.9387          | 0.5974   |
  | 0.9053        | 0.6   | 15000 | 0.9169          | 0.6018   |
  | 0.8942        | 0.8   | 20000 | 0.9233          | 0.6026   |
  | 0.8825        | 1.0   | 25000 | 0.9090          | 0.612    |
  | 0.8161        | 1.2   | 30000 | 0.9296          | 0.608    |
  | 0.7988        | 1.4   | 35000 | 0.9221          | 0.6126   |
  | 0.8326        | 1.6   | 40000 | 0.9112          | 0.6162   |
  | 0.8185        | 1.8   | 45000 | 0.9093          | 0.6168   |
  | 0.8131        | 2.0   | 50000 | 0.9114          | 0.6182   |
  
  
  ### Framework versions
  
  - Transformers 4.22.2
  - Pytorch 1.12.1+cu113
  - Datasets 2.5.1
  - Tokenizers 0.12.1
  