readme: ---
  license: mit
  tags:
  - generated_from_trainer
  model-index:
  - name: recipe-roberta-s
    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-roberta-s
  
  This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.8870
  
  ## 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: 256
  - eval_batch_size: 256
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 20
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss |
  |:-------------:|:-----:|:-----:|:---------------:|
  | 1.3387        | 1.0   | 820   | 1.1529          |
  | 1.187         | 2.0   | 1640  | 1.0643          |
  | 1.1213        | 3.0   | 2460  | 1.0371          |
  | 1.0859        | 4.0   | 3280  | 1.0000          |
  | 1.0566        | 5.0   | 4100  | 0.9798          |
  | 1.0338        | 6.0   | 4920  | 0.9637          |
  | 1.0162        | 7.0   | 5740  | 0.9538          |
  | 1.0003        | 8.0   | 6560  | 0.9332          |
  | 0.9878        | 9.0   | 7380  | 0.9252          |
  | 0.9767        | 10.0  | 8200  | 0.9189          |
  | 0.9664        | 11.0  | 9020  | 0.9145          |
  | 0.9627        | 12.0  | 9840  | 0.9065          |
  | 0.9539        | 13.0  | 10660 | 0.9027          |
  | 0.9461        | 14.0  | 11480 | 0.9029          |
  | 0.9435        | 15.0  | 12300 | 0.8949          |
  | 0.9404        | 16.0  | 13120 | 0.8924          |
  | 0.9359        | 17.0  | 13940 | 0.8874          |
  | 0.9307        | 18.0  | 14760 | 0.8842          |
  | 0.9295        | 19.0  | 15580 | 0.8853          |
  | 0.9263        | 20.0  | 16400 | 0.8870          |
  
  
  ### Framework versions
  
  - Transformers 4.19.0.dev0
  - Pytorch 1.11.0+cu102
  - Datasets 2.3.2
  - Tokenizers 0.12.1
  