readme: ---
  license: mit
  tags:
  - generated_from_trainer
  datasets:
  - emotion
  metrics:
  - accuracy
  model-index:
  - name: deberta-v3-xsmall-emotion
    results:
    - task:
        name: Text Classification
        type: text-classification
      dataset:
        name: emotion
        type: emotion
        args: default
      metrics:
      - name: Accuracy
        type: accuracy
        value: 0.932
  ---
  
  <!-- 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. -->
  
  # deberta-v3-xsmall-emotion
  
  This model is a fine-tuned version of [microsoft/deberta-v3-xsmall](https://huggingface.co/microsoft/deberta-v3-xsmall) on the emotion dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.1877
  - Accuracy: 0.932
  
  ## 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: 3e-05
  - train_batch_size: 32
  - eval_batch_size: 32
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 500
  - num_epochs: 5
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
  | 1.3683        | 1.0   | 500  | 0.8479          | 0.6975   |
  | 0.547         | 2.0   | 1000 | 0.2881          | 0.905    |
  | 0.2378        | 3.0   | 1500 | 0.2116          | 0.925    |
  | 0.1704        | 4.0   | 2000 | 0.1877          | 0.932    |
  | 0.1392        | 5.0   | 2500 | 0.1718          | 0.9295   |
  
  
  ### Framework versions
  
  - Transformers 4.12.3
  - Pytorch 1.9.1
  - Datasets 1.15.1
  - Tokenizers 0.10.3
  