readme: ---
  license: mit
  tags:
  - generated_from_trainer
  model-index:
  - name: recipe-roberta-upper-tIs
    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-upper-tIs
  
  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: 0.7904
  
  ## 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 |
  |:-------------:|:-----:|:-----:|:---------------:|
  | 1.2671        | 1.0   | 1281  | 1.0554          |
  | 1.0995        | 2.0   | 2562  | 0.9832          |
  | 1.0339        | 3.0   | 3843  | 0.9389          |
  | 0.9925        | 4.0   | 5124  | 0.9095          |
  | 0.964         | 5.0   | 6405  | 0.8914          |
  | 0.9426        | 6.0   | 7686  | 0.8708          |
  | 0.9227        | 7.0   | 8967  | 0.8590          |
  | 0.9082        | 8.0   | 10248 | 0.8448          |
  | 0.8963        | 9.0   | 11529 | 0.8361          |
  | 0.8847        | 10.0  | 12810 | 0.8249          |
  | 0.8756        | 11.0  | 14091 | 0.8204          |
  | 0.8672        | 12.0  | 15372 | 0.8105          |
  | 0.8612        | 13.0  | 16653 | 0.8106          |
  | 0.8561        | 14.0  | 17934 | 0.8041          |
  | 0.8485        | 15.0  | 19215 | 0.7979          |
  | 0.8452        | 16.0  | 20496 | 0.7910          |
  | 0.8403        | 17.0  | 21777 | 0.7991          |
  | 0.8389        | 18.0  | 23058 | 0.7928          |
  | 0.8371        | 19.0  | 24339 | 0.7926          |
  | 0.8341        | 20.0  | 25620 | 0.7904          |
  
  
  ### Framework versions
  
  - Transformers 4.19.0.dev0
  - Pytorch 1.11.0+cu102
  - Datasets 2.3.2
  - Tokenizers 0.12.1
  