readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  model-index:
  - name: recipe-gauss-wo-outliers
    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. -->
  
  # recipe-gauss-wo-outliers
  
  This model is a fine-tuned version of [paola-md/recipe-distilroberta-Is](https://huggingface.co/paola-md/recipe-distilroberta-Is) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.2885
  - Rmse: 0.5371
  - Mse: 0.2885
  - Mae: 0.4213
  
  ## 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: 128
  - eval_batch_size: 128
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 10
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Rmse   | Mse    | Mae    |
  |:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|
  | 0.2768        | 1.0   | 1245  | 0.2747          | 0.5241 | 0.2747 | 0.4081 |
  | 0.2737        | 2.0   | 2490  | 0.2793          | 0.5285 | 0.2793 | 0.4288 |
  | 0.2722        | 3.0   | 3735  | 0.2792          | 0.5284 | 0.2792 | 0.4332 |
  | 0.2703        | 4.0   | 4980  | 0.2770          | 0.5263 | 0.2770 | 0.4000 |
  | 0.2682        | 5.0   | 6225  | 0.2758          | 0.5252 | 0.2758 | 0.4183 |
  | 0.2658        | 6.0   | 7470  | 0.2792          | 0.5284 | 0.2792 | 0.4212 |
  | 0.2631        | 7.0   | 8715  | 0.2769          | 0.5262 | 0.2769 | 0.4114 |
  | 0.2599        | 8.0   | 9960  | 0.2802          | 0.5294 | 0.2802 | 0.4107 |
  | 0.2572        | 9.0   | 11205 | 0.2885          | 0.5371 | 0.2885 | 0.4213 |
  
  
  ### Framework versions
  
  - Transformers 4.19.0.dev0
  - Pytorch 1.9.0+cu111
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  