readme: ---
  license: mit
  tags:
  - generated_from_trainer
  metrics:
  - f1
  model-index:
  - name: xlm-roberta-large-finetuned-HC3-mix
    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. -->
  
  # xlm-roberta-large-finetuned-HC3-mix
  
  This model is a fine-tuned version of [xlm-roberta-large](https://huggingface.co/xlm-roberta-large) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.6998
  - F1: 0.0
  
  ## 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: 16
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 5
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step   | Validation Loss | F1  |
  |:-------------:|:-----:|:------:|:---------------:|:---:|
  | 0.6506        | 1.0   | 35824  | 0.6998          | 0.0 |
  | 0.6481        | 2.0   | 71648  | 0.7662          | 0.0 |
  | 0.6391        | 3.0   | 107472 | 0.7492          | 0.0 |
  | 0.6396        | 4.0   | 143296 | 0.7358          | 0.0 |
  | 0.6366        | 5.0   | 179120 | 0.7259          | 0.0 |
  
  
  ### Framework versions
  
  - Transformers 4.26.0
  - Pytorch 1.13.1+cu116
  - Datasets 2.8.0
  - Tokenizers 0.13.2
  