readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  model-index:
  - name: distilbert-base-uncased-finetuned-ft1500_norm300_aug9
    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_aug9
  
  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: 1.0639
  - Mse: 4.2557
  - Mae: 1.3660
  - R2: 0.4773
  - Accuracy: 0.3664
  
  ## 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: 3
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Mse    | Mae    | R2     | Accuracy |
  |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:--------:|
  | 0.7595        | 1.0   | 3242 | 1.1009          | 4.4036 | 1.4148 | 0.4591 | 0.3440   |
  | 0.6024        | 2.0   | 6484 | 1.0896          | 4.3582 | 1.3732 | 0.4647 | 0.3690   |
  | 0.3745        | 3.0   | 9726 | 1.0639          | 4.2557 | 1.3660 | 0.4773 | 0.3664   |
  
  
  ### Framework versions
  
  - Transformers 4.21.1
  - Pytorch 1.12.1+cu113
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  