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Vigec-V5
This model is a fine-tuned version of VietAI/vit5-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.3694
- Bleu: 77.0736
- Gen Len: 10.0475
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: 1e-05
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 10000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Bleu | Gen Len |
|---|---|---|---|---|---|
| 1.195 | 0.01 | 500 | 0.9492 | 43.0845 | 7.2405 |
| 0.978 | 0.01 | 1000 | 0.7804 | 61.0671 | 9.7255 |
| 0.8418 | 0.02 | 1500 | 0.6798 | 64.3811 | 9.9025 |
| 0.8148 | 0.03 | 2000 | 0.6046 | 66.1944 | 10.043 |
| 0.7622 | 0.04 | 2500 | 0.5513 | 68.2851 | 10.1215 |
| 0.7199 | 0.04 | 3000 | 0.5146 | 69.7161 | 10.0795 |
| 0.7898 | 0.05 | 3500 | 0.4869 | 71.1868 | 10.079 |
| 0.6921 | 0.06 | 4000 | 0.4648 | 72.4203 | 10.0345 |
| 0.6827 | 0.07 | 4500 | 0.4490 | 73.2133 | 10.039 |
| 0.6102 | 0.07 | 5000 | 0.4355 | 73.6841 | 10.078 |
| 0.5805 | 0.08 | 5500 | 0.4176 | 74.2559 | 10.059 |
| 0.6806 | 0.09 | 6000 | 0.4081 | 74.7389 | 10.0655 |
| 0.6544 | 0.09 | 6500 | 0.3958 | 75.2603 | 10.025 |
| 0.6244 | 0.1 | 7000 | 0.3904 | 75.9306 | 10.0565 |
| 0.7212 | 0.11 | 7500 | 0.3822 | 76.3268 | 10.0505 |
| 0.5446 | 0.12 | 8000 | 0.3785 | 76.5306 | 10.0505 |
| 0.5574 | 0.12 | 8500 | 0.3741 | 76.7101 | 10.0545 |
| 0.6265 | 0.13 | 9000 | 0.3721 | 76.8858 | 10.043 |
| 0.5379 | 0.14 | 9500 | 0.3695 | 77.001 | 10.051 |
| 0.6164 | 0.14 | 10000 | 0.3694 | 77.0736 | 10.0475 |
Framework versions
- Transformers 4.26.0
- Pytorch 1.13.1+cu116
- Datasets 2.9.0
- Tokenizers 0.13.2
