readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  model-index:
  - name: distilbert-base-uncased-Regression-Simpsons_Plus_Others
    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-Regression-Simpsons_Plus_Others
  
  This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.3754
  - Mse: 0.3754
  - Rmse: 0.6127
  - Mae: 0.4651
  
  ## 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: 64
  - eval_batch_size: 64
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 25
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Mse    | Rmse   | Mae    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|
  | 29.5977       | 1.0   | 51   | 7.9215          | 7.9215 | 2.8145 | 2.7032 |
  | 4.4551        | 2.0   | 102  | 0.6728          | 0.6728 | 0.8202 | 0.6039 |
  | 2.0068        | 3.0   | 153  | 0.6034          | 0.6034 | 0.7768 | 0.5882 |
  | 1.8734        | 4.0   | 204  | 0.4423          | 0.4423 | 0.6651 | 0.4975 |
  | 1.7607        | 5.0   | 255  | 0.3971          | 0.3971 | 0.6302 | 0.4725 |
  | 1.6901        | 6.0   | 306  | 0.4005          | 0.4005 | 0.6328 | 0.4751 |
  | 1.6525        | 7.0   | 357  | 0.4001          | 0.4001 | 0.6325 | 0.4766 |
  | 1.6103        | 8.0   | 408  | 0.4278          | 0.4278 | 0.6541 | 0.4954 |
  | 1.5659        | 9.0   | 459  | 0.3903          | 0.3903 | 0.6247 | 0.4618 |
  | 1.4968        | 10.0  | 510  | 0.3987          | 0.3987 | 0.6314 | 0.4670 |
  | 1.4983        | 11.0  | 561  | 0.4764          | 0.4764 | 0.6902 | 0.5324 |
  | 1.4659        | 12.0  | 612  | 0.3913          | 0.3913 | 0.6256 | 0.4616 |
  | 1.4532        | 13.0  | 663  | 0.4511          | 0.4511 | 0.6716 | 0.5153 |
  | 1.4515        | 14.0  | 714  | 0.4009          | 0.4009 | 0.6332 | 0.4768 |
  | 1.4506        | 15.0  | 765  | 0.4588          | 0.4588 | 0.6773 | 0.5160 |
  | 1.4249        | 16.0  | 816  | 0.3940          | 0.3940 | 0.6277 | 0.4630 |
  | 1.4254        | 17.0  | 867  | 0.4456          | 0.4456 | 0.6675 | 0.5084 |
  | 1.4023        | 18.0  | 918  | 0.4517          | 0.4517 | 0.6721 | 0.5096 |
  | 1.3754        | 19.0  | 969  | 0.4210          | 0.4210 | 0.6489 | 0.4869 |
  | 1.3865        | 20.0  | 1020 | 0.4163          | 0.4163 | 0.6452 | 0.4830 |
  | 1.3802        | 21.0  | 1071 | 0.4290          | 0.4290 | 0.6550 | 0.4904 |
  | 1.4087        | 22.0  | 1122 | 0.4097          | 0.4097 | 0.6401 | 0.4745 |
  | 1.3855        | 23.0  | 1173 | 0.4438          | 0.4438 | 0.6662 | 0.5027 |
  | 1.3911        | 24.0  | 1224 | 0.4302          | 0.4302 | 0.6559 | 0.4906 |
  | 1.3877        | 25.0  | 1275 | 0.4287          | 0.4287 | 0.6547 | 0.4887 |
  
  
  ### Framework versions
  
  - Transformers 4.22.1
  - Pytorch 1.12.1
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  