readme: ---
  license: mit
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  model-index:
  - name: deberta-v3-large__sst2__train-16-0
    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-v3-large__sst2__train-16-0
  
  This model is a fine-tuned version of [microsoft/deberta-v3-large](https://huggingface.co/microsoft/deberta-v3-large) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.9917
  - Accuracy: 0.7705
  
  ## 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: 4
  - eval_batch_size: 4
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 50
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
  | 0.7001        | 1.0   | 7    | 0.7327          | 0.2857   |
  | 0.6326        | 2.0   | 14   | 0.6479          | 0.5714   |
  | 0.5232        | 3.0   | 21   | 0.5714          | 0.5714   |
  | 0.3313        | 4.0   | 28   | 0.6340          | 0.7143   |
  | 0.3161        | 5.0   | 35   | 0.6304          | 0.7143   |
  | 0.0943        | 6.0   | 42   | 0.4719          | 0.8571   |
  | 0.0593        | 7.0   | 49   | 0.5000          | 0.7143   |
  | 0.0402        | 8.0   | 56   | 0.3530          | 0.8571   |
  | 0.0307        | 9.0   | 63   | 0.3499          | 0.8571   |
  | 0.0033        | 10.0  | 70   | 0.3258          | 0.8571   |
  | 0.0021        | 11.0  | 77   | 0.3362          | 0.8571   |
  | 0.0012        | 12.0  | 84   | 0.4591          | 0.8571   |
  | 0.0036        | 13.0  | 91   | 0.4661          | 0.8571   |
  | 0.001         | 14.0  | 98   | 0.5084          | 0.8571   |
  | 0.0017        | 15.0  | 105  | 0.5844          | 0.8571   |
  | 0.0005        | 16.0  | 112  | 0.6645          | 0.8571   |
  | 0.002         | 17.0  | 119  | 0.7422          | 0.8571   |
  | 0.0006        | 18.0  | 126  | 0.7354          | 0.8571   |
  | 0.0005        | 19.0  | 133  | 0.7265          | 0.8571   |
  | 0.0005        | 20.0  | 140  | 0.7207          | 0.8571   |
  
  
  ### Framework versions
  
  - Transformers 4.15.0
  - Pytorch 1.10.2+cu102
  - Datasets 1.18.2
  - Tokenizers 0.10.3
  