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xlm-roberta-base-Final_VietNam-aug_insert_w2v-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: 1.2040
- Accuracy: 0.72
- F1: 0.7257
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 |
|---|---|---|---|---|---|
| 0.9886 | 1.0 | 85 | 0.7499 | 0.65 | 0.5970 |
| 0.6861 | 2.0 | 170 | 0.7312 | 0.7 | 0.7029 |
| 0.5673 | 3.0 | 255 | 0.6732 | 0.73 | 0.7328 |
| 0.4086 | 4.0 | 340 | 0.8771 | 0.73 | 0.7308 |
| 0.2958 | 5.0 | 425 | 0.9051 | 0.74 | 0.7453 |
| 0.2039 | 6.0 | 510 | 1.0350 | 0.73 | 0.7314 |
| 0.1743 | 7.0 | 595 | 1.1745 | 0.7 | 0.7097 |
| 0.1458 | 8.0 | 680 | 1.2040 | 0.72 | 0.7257 |
Framework versions
- Transformers 4.33.1
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3
