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xlm-roberta-base-Mixed-insert-vi
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: 1.0718
- Accuracy: 0.8169
- F1: 0.8133
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: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 0.7982 | 1.0 | 213 | 0.6740 | 0.7625 | 0.7024 |
| 0.5276 | 2.0 | 426 | 0.5662 | 0.7943 | 0.7859 |
| 0.4071 | 3.0 | 639 | 0.5453 | 0.7958 | 0.7929 |
| 0.3311 | 4.0 | 852 | 0.5844 | 0.8094 | 0.8007 |
| 0.2695 | 5.0 | 1065 | 0.5819 | 0.8230 | 0.8221 |
| 0.2226 | 6.0 | 1278 | 0.7325 | 0.8200 | 0.8144 |
| 0.1826 | 7.0 | 1491 | 0.8314 | 0.8124 | 0.8070 |
| 0.1469 | 8.0 | 1704 | 0.9560 | 0.8154 | 0.8124 |
| 0.1397 | 9.0 | 1917 | 1.0850 | 0.8169 | 0.8105 |
| 0.1231 | 10.0 | 2130 | 1.0718 | 0.8169 | 0.8133 |
Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3
