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xlm-roberta-base-Final_Mixed-aug_swap-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: 1.2104
- Accuracy: 0.75
- F1: 0.7434
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 |
|---|---|---|---|---|---|
| 1.0503 | 1.0 | 87 | 0.9473 | 0.62 | 0.5062 |
| 0.7772 | 2.0 | 174 | 0.6460 | 0.74 | 0.7214 |
| 0.5668 | 3.0 | 261 | 0.6739 | 0.76 | 0.7474 |
| 0.3978 | 4.0 | 348 | 0.7077 | 0.78 | 0.7737 |
| 0.2502 | 5.0 | 435 | 1.0460 | 0.75 | 0.7340 |
| 0.1757 | 6.0 | 522 | 1.0285 | 0.74 | 0.7355 |
| 0.1439 | 7.0 | 609 | 1.1870 | 0.75 | 0.7454 |
| 0.1178 | 8.0 | 696 | 1.2104 | 0.75 | 0.7434 |
Framework versions
- Transformers 4.33.1
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3
