readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  model-index:
  - name: recipistil
    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. -->
  
  # recipistil
  
  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: 1.9743
  - Rmse: 1.4051
  - Mse: 1.9743
  - Mae: 1.0578
  
  ## 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: 5e-05
  - train_batch_size: 16
  - eval_batch_size: 16
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 15
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Rmse   | Mse    | Mae    |
  |:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|
  | 1.9657        | 1.0   | 8126  | 1.9789          | 1.4067 | 1.9789 | 1.0578 |
  | 1.9617        | 2.0   | 16252 | 1.9873          | 1.4097 | 1.9873 | 1.0620 |
  | 1.9588        | 3.0   | 24378 | 1.9769          | 1.4060 | 1.9769 | 1.0578 |
  | 1.958         | 4.0   | 32504 | 1.9736          | 1.4048 | 1.9736 | 1.0578 |
  | 1.9568        | 5.0   | 40630 | 1.9772          | 1.4061 | 1.9772 | 1.0578 |
  | 1.9564        | 6.0   | 48756 | 1.9736          | 1.4048 | 1.9736 | 1.0578 |
  | 1.9563        | 7.0   | 56882 | 1.9737          | 1.4049 | 1.9737 | 1.0578 |
  | 1.9561        | 8.0   | 65008 | 1.9737          | 1.4049 | 1.9737 | 1.0578 |
  | 1.9559        | 9.0   | 73134 | 1.9743          | 1.4051 | 1.9743 | 1.0578 |
  
  
  ### Framework versions
  
  - Transformers 4.19.0.dev0
  - Pytorch 1.9.0+cu111
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  