readme: ---
  license: mit
  tags:
  - generated_from_trainer
  model-index:
  - name: roberta-base-lm-all
    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. -->
  
  # roberta-base-lm-all
  
  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: 0.7109
  
  ## 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: 32
  - eval_batch_size: 8
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 16
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss |
  |:-------------:|:-----:|:-----:|:---------------:|
  | 1.2966        | 1.0   | 1194  | 1.0711          |
  | 1.0858        | 2.0   | 2388  | 0.9740          |
  | 1.0055        | 3.0   | 3582  | 0.9273          |
  | 0.9301        | 4.0   | 4776  | 0.8784          |
  | 0.9021        | 5.0   | 5970  | 0.8731          |
  | 0.8479        | 6.0   | 7164  | 0.8406          |
  | 0.8142        | 7.0   | 8358  | 0.8172          |
  | 0.7858        | 8.0   | 9552  | 0.8158          |
  | 0.7529        | 9.0   | 10746 | 0.7922          |
  | 0.7189        | 10.0  | 11940 | 0.7855          |
  | 0.7032        | 11.0  | 13134 | 0.7761          |
  | 0.6795        | 12.0  | 14328 | 0.7549          |
  | 0.6673        | 13.0  | 15522 | 0.7277          |
  | 0.6412        | 14.0  | 16716 | 0.7121          |
  | 0.6321        | 15.0  | 17910 | 0.7168          |
  | 0.6198        | 16.0  | 19104 | 0.7109          |
  
  
  ### Framework versions
  
  - Transformers 4.21.2
  - Pytorch 1.12.1+cu113
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  