readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  model-index:
  - name: recipe-gauss-3
    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-3
  
  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: 0.2729
  - Rmse: 0.5224
  - Mse: 0.2729
  - Mae: 0.3977
  
  ## 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    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|
  | 0.2602        | 1.0   | 745  | 0.2613          | 0.5112 | 0.2613 | 0.4000 |
  | 0.2562        | 2.0   | 1490 | 0.2595          | 0.5094 | 0.2595 | 0.3958 |
  | 0.2542        | 3.0   | 2235 | 0.2595          | 0.5094 | 0.2595 | 0.3932 |
  | 0.2521        | 4.0   | 2980 | 0.2615          | 0.5114 | 0.2615 | 0.4016 |
  | 0.2503        | 5.0   | 3725 | 0.2594          | 0.5093 | 0.2594 | 0.3913 |
  | 0.2473        | 6.0   | 4470 | 0.2641          | 0.5139 | 0.2641 | 0.3834 |
  | 0.244         | 7.0   | 5215 | 0.2649          | 0.5147 | 0.2649 | 0.3986 |
  | 0.2401        | 8.0   | 5960 | 0.2661          | 0.5158 | 0.2661 | 0.3906 |
  | 0.2359        | 9.0   | 6705 | 0.2693          | 0.5189 | 0.2693 | 0.3946 |
  | 0.2332        | 10.0  | 7450 | 0.2729          | 0.5224 | 0.2729 | 0.3977 |
  
  
  ### Framework versions
  
  - Transformers 4.19.0.dev0
  - Pytorch 1.9.0+cu111
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  