readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  model-index:
  - name: distilbert-base-uncased__sst2__train-16-5
    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. -->
  
  # distilbert-base-uncased__sst2__train-16-5
  
  This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.6537
  - Accuracy: 0.6332
  
  ## 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 |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
  | 0.6925        | 1.0   | 7    | 0.6966          | 0.2857   |
  | 0.6703        | 2.0   | 14   | 0.7045          | 0.2857   |
  | 0.6404        | 3.0   | 21   | 0.7205          | 0.2857   |
  | 0.555         | 4.0   | 28   | 0.7548          | 0.2857   |
  | 0.5179        | 5.0   | 35   | 0.6745          | 0.5714   |
  | 0.3038        | 6.0   | 42   | 0.7260          | 0.5714   |
  | 0.2089        | 7.0   | 49   | 0.8016          | 0.5714   |
  | 0.1303        | 8.0   | 56   | 0.8202          | 0.5714   |
  | 0.0899        | 9.0   | 63   | 0.9966          | 0.5714   |
  | 0.0552        | 10.0  | 70   | 1.1887          | 0.5714   |
  | 0.0333        | 11.0  | 77   | 1.2163          | 0.5714   |
  | 0.0169        | 12.0  | 84   | 1.2874          | 0.5714   |
  | 0.0136        | 13.0  | 91   | 1.3598          | 0.5714   |
  | 0.0103        | 14.0  | 98   | 1.4237          | 0.5714   |
  | 0.0089        | 15.0  | 105  | 1.4758          | 0.5714   |
  
  
  ### Framework versions
  
  - Transformers 4.15.0
  - Pytorch 1.10.2+cu102
  - Datasets 1.18.2
  - Tokenizers 0.10.3
  