readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  model-index:
  - name: distilbert-base-uncased-finetuned-ft1500_reg3
    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_reg3
  
  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: 0.7954
  - Mse: 0.7954
  - Mae: 0.6900
  - R2: 0.4769
  - Accuracy: 0.4459
  
  ## 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 |
  |:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:--------:|
  | 1.018         | 1.0   | 3122  | 0.7491          | 0.7491 | 0.6739 | 0.5073 | 0.4555   |
  | 0.668         | 2.0   | 6244  | 0.7397          | 0.7397 | 0.6687 | 0.5135 | 0.4689   |
  | 0.4871        | 3.0   | 9366  | 0.7542          | 0.7542 | 0.6730 | 0.5040 | 0.4606   |
  | 0.3419        | 4.0   | 12488 | 0.7710          | 0.7710 | 0.6802 | 0.4929 | 0.4536   |
  | 0.2532        | 5.0   | 15610 | 0.7954          | 0.7954 | 0.6900 | 0.4769 | 0.4459   |
  
  
  ### Framework versions
  
  - Transformers 4.21.0
  - Pytorch 1.12.0+cu113
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  