readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  model-index:
  - name: distilbert-base-uncased__sst2__train-16-2
    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-16-2
  
  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: 0.6748
  - Accuracy: 0.6315
  
  ## 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 |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
  | 0.7043        | 1.0   | 7    | 0.7054          | 0.2857   |
  | 0.6711        | 2.0   | 14   | 0.7208          | 0.2857   |
  | 0.6311        | 3.0   | 21   | 0.7365          | 0.2857   |
  | 0.551         | 4.0   | 28   | 0.7657          | 0.5714   |
  | 0.5599        | 5.0   | 35   | 0.6915          | 0.5714   |
  | 0.3167        | 6.0   | 42   | 0.7134          | 0.5714   |
  | 0.2489        | 7.0   | 49   | 0.7892          | 0.5714   |
  | 0.1985        | 8.0   | 56   | 0.6756          | 0.7143   |
  | 0.0864        | 9.0   | 63   | 0.8059          | 0.5714   |
  | 0.0903        | 10.0  | 70   | 0.8165          | 0.7143   |
  | 0.0429        | 11.0  | 77   | 0.7947          | 0.7143   |
  | 0.0186        | 12.0  | 84   | 0.8570          | 0.7143   |
  | 0.0146        | 13.0  | 91   | 0.9346          | 0.7143   |
  | 0.011         | 14.0  | 98   | 0.9804          | 0.7143   |
  | 0.0098        | 15.0  | 105  | 1.0136          | 0.7143   |
  | 0.0086        | 16.0  | 112  | 1.0424          | 0.7143   |
  | 0.0089        | 17.0  | 119  | 1.0736          | 0.7143   |
  | 0.0068        | 18.0  | 126  | 1.0808          | 0.7143   |
  
  
  ### Framework versions
  
  - Transformers 4.15.0
  - Pytorch 1.10.2+cu102
  - Datasets 1.18.2
  - Tokenizers 0.10.3
  