readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  model-index:
  - name: distilbert-base-uncased-finetuned-ft1500_norm500_aug1
    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-finetuned-ft1500_norm500_aug1
  
  This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 2.9086
  - Mse: 3.6357
  - Mae: 1.0762
  - R2: 0.2894
  - Accuracy: 0.5170
  
  ## 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: 5
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Mse    | Mae    | R2     | Accuracy |
  |:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:--------:|
  | 1.5856        | 1.0   | 5847  | 3.3101          | 4.1376 | 1.1447 | 0.1913 | 0.4965   |
  | 0.442         | 2.0   | 11694 | 2.7448          | 3.4311 | 1.0934 | 0.3294 | 0.4523   |
  | 0.2703        | 3.0   | 17541 | 2.9300          | 3.6625 | 1.0907 | 0.2841 | 0.4933   |
  | 0.1699        | 4.0   | 23388 | 2.7979          | 3.4973 | 1.0808 | 0.3164 | 0.4805   |
  | 0.1168        | 5.0   | 29235 | 2.9086          | 3.6357 | 1.0762 | 0.2894 | 0.5170   |
  
  
  ### Framework versions
  
  - Transformers 4.21.1
  - Pytorch 1.12.0+cu113
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  