readme: ---
  license: mit
  tags:
  - fill-mask
  - generated_from_trainer
  metrics:
  - accuracy
  model-index:
  - name: deberta-mlm-test
    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. -->
  
  # deberta-mlm-test
  
  This model is a fine-tuned version of [microsoft/deberta-v3-xsmall](https://huggingface.co/microsoft/deberta-v3-xsmall) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 3.2792
  - Accuracy: 0.4766
  
  ## 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: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 5
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Accuracy |
  |:-------------:|:-----:|:-----:|:---------------:|:--------:|
  | 4.4466        | 1.0   | 2067  | 4.1217          | 0.3847   |
  | 3.9191        | 2.0   | 4134  | 3.6562          | 0.4298   |
  | 3.6397        | 3.0   | 6201  | 3.4417          | 0.4550   |
  | 3.522         | 4.0   | 8268  | 3.3239          | 0.4692   |
  | 3.4504        | 5.0   | 10335 | 3.2792          | 0.4766   |
  
  
  ### Framework versions
  
  - Transformers 4.20.1
  - Pytorch 1.11.0a0+17540c5
  - Datasets 2.3.2
  - Tokenizers 0.12.1
  