metadata
base_model: vinai/phobert-base-v2
tags:
- generated_from_trainer
model-index:
- name: phobert-base-v2-ed
results: []
phobert-base-v2-ed
This model is a fine-tuned version of vinai/phobert-base-v2 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0455
- F1 Micro: 0.7302
- F1 Macro: 0.0774
- Recall Micro: 0.6299
- Precision Micro: 0.8683
- Recall Macro: 0.0745
- Precision Macro: 0.0806
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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 Micro | F1 Macro | Recall Micro | Precision Micro | Recall Macro | Precision Macro |
|---|---|---|---|---|---|---|---|---|---|
| 0.0638 | 1.0 | 1526 | 0.0622 | 0.7114 | 0.0257 | 0.6218 | 0.8312 | 0.0271 | 0.0244 |
| 0.046 | 2.0 | 3052 | 0.0543 | 0.7112 | 0.0259 | 0.6021 | 0.8684 | 0.0263 | 0.0255 |
| 0.0462 | 3.0 | 4578 | 0.0494 | 0.7049 | 0.0716 | 0.5895 | 0.8764 | 0.0685 | 0.0803 |
| 0.0472 | 4.0 | 6104 | 0.0461 | 0.7326 | 0.0762 | 0.6402 | 0.8562 | 0.0724 | 0.0812 |
| 0.0228 | 5.0 | 7630 | 0.0455 | 0.7302 | 0.0774 | 0.6299 | 0.8683 | 0.0745 | 0.0806 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1