readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  model-index:
  - name: distilbert-base-uncased__sst2__train-8-4
    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-8-4
  
  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: 0.6921
  - Accuracy: 0.5107
  
  ## 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 |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
  | 0.7163        | 1.0   | 3    | 0.7100          | 0.25     |
  | 0.6785        | 2.0   | 6    | 0.7209          | 0.25     |
  | 0.6455        | 3.0   | 9    | 0.7321          | 0.25     |
  | 0.6076        | 4.0   | 12   | 0.7517          | 0.25     |
  | 0.5593        | 5.0   | 15   | 0.7780          | 0.25     |
  | 0.5202        | 6.0   | 18   | 0.7990          | 0.25     |
  | 0.4967        | 7.0   | 21   | 0.8203          | 0.25     |
  | 0.4158        | 8.0   | 24   | 0.8497          | 0.25     |
  | 0.3997        | 9.0   | 27   | 0.8638          | 0.25     |
  | 0.3064        | 10.0  | 30   | 0.8732          | 0.25     |
  | 0.2618        | 11.0  | 33   | 0.8669          | 0.25     |
  
  
  ### Framework versions
  
  - Transformers 4.15.0
  - Pytorch 1.10.2+cu102
  - Datasets 1.18.2
  - Tokenizers 0.10.3
  