readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  model-index:
  - name: distilbert-base-uncased-finetuned-ft1500_norm300
    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_norm300
  
  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: 1.0940
  - Mse: 4.3760
  - Mae: 1.4084
  - R2: 0.4625
  - Accuracy: 0.3517
  
  ## 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: 4
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Mse    | Mae    | R2     | Accuracy |
  |:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:--------:|
  | 0.7424        | 1.0   | 3122  | 1.1071          | 4.4286 | 1.4098 | 0.4561 | 0.3338   |
  | 0.5038        | 2.0   | 6244  | 1.1794          | 4.7177 | 1.4140 | 0.4205 | 0.3677   |
  | 0.356         | 3.0   | 9366  | 1.0717          | 4.2866 | 1.3852 | 0.4735 | 0.3581   |
  | 0.2293        | 4.0   | 12488 | 1.0940          | 4.3760 | 1.4084 | 0.4625 | 0.3517   |
  
  
  ### Framework versions
  
  - Transformers 4.21.1
  - Pytorch 1.12.0+cu113
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  