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xlm-roberta-large-finetuned-HC3-mix
This model is a fine-tuned version of 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
