readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  model-index:
  - name: distilbert-base-uncased__sst2__train-8-2
    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-8-2
  
  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: 0.6932
  - Accuracy: 0.4931
  
  ## 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 |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
  | 0.7081        | 1.0   | 3    | 0.7031          | 0.25     |
  | 0.6853        | 2.0   | 6    | 0.7109          | 0.25     |
  | 0.6696        | 3.0   | 9    | 0.7211          | 0.25     |
  | 0.6174        | 4.0   | 12   | 0.7407          | 0.25     |
  | 0.5717        | 5.0   | 15   | 0.7625          | 0.25     |
  | 0.5096        | 6.0   | 18   | 0.7732          | 0.25     |
  | 0.488         | 7.0   | 21   | 0.7798          | 0.25     |
  | 0.4023        | 8.0   | 24   | 0.7981          | 0.25     |
  | 0.3556        | 9.0   | 27   | 0.8110          | 0.25     |
  | 0.2714        | 10.0  | 30   | 0.8269          | 0.25     |
  | 0.2295        | 11.0  | 33   | 0.8276          | 0.25     |
  
  
  ### Framework versions
  
  - Transformers 4.15.0
  - Pytorch 1.10.2+cu102
  - Datasets 1.18.2
  - Tokenizers 0.10.3
  