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xlm-roberta-base-Final_Mixed-aug_backtranslation
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: 1.2392
- Accuracy: 0.71
- F1: 0.7021
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: 8
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 1.0111 | 1.0 | 87 | 0.8146 | 0.64 | 0.5888 |
| 0.7211 | 2.0 | 174 | 0.7209 | 0.74 | 0.7347 |
| 0.5231 | 3.0 | 261 | 0.8348 | 0.7 | 0.6778 |
| 0.3879 | 4.0 | 348 | 0.7918 | 0.75 | 0.7462 |
| 0.3063 | 5.0 | 435 | 0.9875 | 0.7 | 0.6906 |
| 0.2411 | 6.0 | 522 | 1.1185 | 0.72 | 0.7144 |
| 0.2316 | 7.0 | 609 | 1.1889 | 0.69 | 0.6845 |
| 0.1868 | 8.0 | 696 | 1.2392 | 0.71 | 0.7021 |
Framework versions
- Transformers 4.32.1
- Pytorch 2.0.0
- Datasets 2.14.4
- Tokenizers 0.13.3
