readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  model-index:
  - name: distilbert-base-uncased-finetuned-ft1500_reg2
    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_reg2
  
  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: 0.7256
  - Mse: 0.7256
  - Mae: 0.6674
  - R2: 0.4579
  - Accuracy: 0.4573
  
  ## 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 |
  |:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:--------:|
  | 1.0689        | 1.0   | 3000  | 0.7823          | 0.7823 | 0.6948 | 0.4156 | 0.4327   |
  | 0.6733        | 2.0   | 6000  | 0.7286          | 0.7286 | 0.6705 | 0.4556 | 0.4447   |
  | 0.4735        | 3.0   | 9000  | 0.7125          | 0.7125 | 0.6658 | 0.4677 | 0.46     |
  | 0.3358        | 4.0   | 12000 | 0.7256          | 0.7256 | 0.6674 | 0.4579 | 0.4573   |
  
  
  ### Framework versions
  
  - Transformers 4.21.0
  - Pytorch 1.12.0+cu113
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  