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xlm-roberta-base-Final_Mixed-aug_backtranslation-1
This model is a fine-tuned version of xlm-roberta-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.3364
- Accuracy: 0.7
- F1: 0.6913
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: 41
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 8
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 0.9909 | 1.0 | 87 | 0.8850 | 0.6 | 0.5586 |
| 0.7303 | 2.0 | 174 | 0.6941 | 0.69 | 0.6767 |
| 0.5713 | 3.0 | 261 | 0.7149 | 0.73 | 0.7215 |
| 0.4254 | 4.0 | 348 | 0.6955 | 0.75 | 0.7492 |
| 0.331 | 5.0 | 435 | 0.9854 | 0.69 | 0.6737 |
| 0.2373 | 6.0 | 522 | 1.0423 | 0.7 | 0.6909 |
| 0.1995 | 7.0 | 609 | 1.2707 | 0.69 | 0.6806 |
| 0.1713 | 8.0 | 696 | 1.3364 | 0.7 | 0.6913 |
Framework versions
- Transformers 4.33.1
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3
