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viettel-videberta-finetune-viquad-model3
This model is a fine-tuned version of Fsoft-AIC/videberta-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 2.9680
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: 12
- eval_batch_size: 12
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.05
- num_epochs: 2
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 4.6436 | 0.37 | 600 | 3.4906 |
| 3.3933 | 0.74 | 1200 | 3.2496 |
| 3.161 | 1.11 | 1800 | 3.1334 |
| 2.9609 | 1.48 | 2400 | 3.0392 |
| 2.9119 | 1.85 | 3000 | 2.9680 |
Framework versions
- Transformers 4.28.0
- Pytorch 2.0.0+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3
