readme: ---
  license: mit
  tags:
  - generated_from_trainer
  model-index:
  - name: roberta-large-with-labeled-data-and-unlabeled-gab-reddit-semeval2023-task10-13300-labeled-sample
    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-large-with-labeled-data-and-unlabeled-gab-reddit-semeval2023-task10-13300-labeled-sample
  
  This model is a fine-tuned version of [HPL/roberta-large-unlabeled-gab-reddit-semeval2023-task10-57000sample](https://huggingface.co/HPL/roberta-large-unlabeled-gab-reddit-semeval2023-task10-57000sample) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 1.7889
  
  ## 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: 16
  - eval_batch_size: 8
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 4
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss |
  |:-------------:|:-----:|:----:|:---------------:|
  | 1.9921        | 1.0   | 832  | 1.9311          |
  | 1.9284        | 2.0   | 1664 | 1.8428          |
  | 1.8741        | 3.0   | 2496 | 1.8364          |
  | 1.816         | 4.0   | 3328 | 1.7889          |
  
  
  ### Framework versions
  
  - Transformers 4.13.0
  - Pytorch 1.12.1+cu113
  - Datasets 2.7.0
  - Tokenizers 0.10.3
  