readme: ---
  license: mit
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  - f1
  model-index:
  - name: deberta-base-CoLA
    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-base-CoLA
  
  This model is a fine-tuned version of [microsoft/deberta-base](https://huggingface.co/microsoft/deberta-base) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 1.1655
  - Accuracy: 0.8482
  - F1: 0.8961
  - Roc Auc: 0.8987
  - Mcc: 0.6288
  
  ## 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
  - lr_scheduler_warmup_ratio: 0.05
  - num_epochs: 10
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Roc Auc | Mcc    |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:-------:|:------:|
  | 0.5266        | 1.0   | 535  | 0.4138          | 0.8159   | 0.8698 | 0.8627  | 0.5576 |
  | 0.3523        | 2.0   | 1070 | 0.3852          | 0.8387   | 0.8880 | 0.9041  | 0.6070 |
  | 0.2479        | 3.0   | 1605 | 0.3981          | 0.8482   | 0.8901 | 0.9120  | 0.6447 |
  | 0.1712        | 4.0   | 2140 | 0.4732          | 0.8558   | 0.9008 | 0.9160  | 0.6486 |
  | 0.1354        | 5.0   | 2675 | 0.7181          | 0.8463   | 0.8938 | 0.9024  | 0.6250 |
  | 0.0876        | 6.0   | 3210 | 0.8453          | 0.8520   | 0.8992 | 0.9123  | 0.6385 |
  | 0.0682        | 7.0   | 3745 | 1.0282          | 0.8444   | 0.8938 | 0.9061  | 0.6189 |
  | 0.0431        | 8.0   | 4280 | 1.1114          | 0.8463   | 0.8960 | 0.9010  | 0.6239 |
  | 0.0323        | 9.0   | 4815 | 1.1663          | 0.8501   | 0.8970 | 0.8967  | 0.6340 |
  | 0.0163        | 10.0  | 5350 | 1.1655          | 0.8482   | 0.8961 | 0.8987  | 0.6288 |
  
  
  ### Framework versions
  
  - Transformers 4.11.0
  - Pytorch 1.9.0+cu102
  - Datasets 1.12.1
  - Tokenizers 0.10.3
  