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viettel-videberta-finetune-viquad-model9
This model is a fine-tuned version of Fsoft-AIC/videberta-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 2.6069
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: 5e-05
- train_batch_size: 28
- eval_batch_size: 28
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 4
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| No log | 0.58 | 400 | 3.4447 |
| 4.425 | 1.15 | 800 | 3.0804 |
| 2.9522 | 1.73 | 1200 | 2.8190 |
| 2.6361 | 2.31 | 1600 | 2.6903 |
| 2.4279 | 2.88 | 2000 | 2.6549 |
| 2.4279 | 3.46 | 2400 | 2.6069 |
Framework versions
- Transformers 4.28.0
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.13.3
