readme: ---
  license: cc-by-sa-4.0
  tags:
  - generated_from_trainer
  model-index:
  - name: roberta-base-academic
    results: []
  datasets:
  - orieg/elsevier-oa-cc-by
  ---
  
  <!-- 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-academic
  
  This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on a combination of Elsevier OA CC-by dataset and other corpora of university essays such as [BAWE](https://www.coventry.ac.uk/research/research-directories/current-projects/2015/british-academic-written-english-corpus-bawe/) and [MICUSP](https://elicorpora.info/main).
  It achieves the following results on the evaluation set:
  - Loss: 1.4229
  
  ## 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: 0.0001
  - train_batch_size: 8
  - eval_batch_size: 8
  - seed: 42
  - gradient_accumulation_steps: 16
  - total_train_batch_size: 128
  - optimizer: Adam with betas=(0.9,0.99) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_ratio: 0.1
  - num_epochs: 10
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss |
  |:-------------:|:-----:|:----:|:---------------:|
  | 1.671         | 1.0   | 338  | 1.5581          |
  | 1.6395        | 1.99  | 676  | 1.5276          |
  | 1.5991        | 2.99  | 1014 | 1.5108          |
  | 1.5659        | 3.99  | 1352 | 1.4903          |
  | 1.5393        | 4.99  | 1690 | 1.4668          |
  | 1.5178        | 5.98  | 2028 | 1.4621          |
  | 1.4962        | 6.98  | 2366 | 1.4388          |
  | 1.4783        | 7.98  | 2704 | 1.4320          |
  | 1.4652        | 8.97  | 3042 | 1.4216          |
  | 1.4542        | 9.97  | 3380 | 1.4180          |
  
  
  ### Framework versions
  
  - Transformers 4.25.1
  - Pytorch 1.13.0+cu116
  - Datasets 2.8.0
  - Tokenizers 0.13.2