viettel-phobert-finetune-viquad-model2
This model is a fine-tuned version of vinai/phobert-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.2241
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: 20
- eval_batch_size: 20
- seed: 42
- gradient_accumulation_steps: 3
- total_train_batch_size: 60
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 4
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| No log | 0.57 | 200 | 1.9861 |
| No log | 1.13 | 400 | 1.4553 |
| 2.436 | 1.7 | 600 | 1.3003 |
| 2.436 | 2.26 | 800 | 1.2814 |
| 1.1594 | 2.83 | 1000 | 1.2354 |
| 1.1594 | 3.39 | 1200 | 1.2319 |
| 1.1594 | 3.96 | 1400 | 1.2241 |
Framework versions
- Transformers 4.28.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3