readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  model-index:
  - name: distilbert-base-uncased-finetuned-ft1500_norm1000
    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_norm1000
  
  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: 1.0875
  - Mse: 1.3594
  - Mae: 0.5794
  - R2: 0.3573
  - Accuracy: 0.7015
  
  ## 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 |
  |:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:--------:|
  | 0.8897        | 1.0   | 3122  | 1.0463          | 1.3078 | 0.5936 | 0.3817 | 0.7008   |
  | 0.7312        | 2.0   | 6244  | 1.0870          | 1.3588 | 0.5796 | 0.3576 | 0.7002   |
  | 0.5348        | 3.0   | 9366  | 1.1056          | 1.3820 | 0.5786 | 0.3467 | 0.7124   |
  | 0.3693        | 4.0   | 12488 | 1.0866          | 1.3582 | 0.5854 | 0.3579 | 0.7053   |
  | 0.2848        | 5.0   | 15610 | 1.0875          | 1.3594 | 0.5794 | 0.3573 | 0.7015   |
  
  
  ### Framework versions
  
  - Transformers 4.21.0
  - Pytorch 1.12.0+cu113
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  