|
|
--- |
|
|
library_name: transformers |
|
|
license: mit |
|
|
base_model: vinai/phobert-base |
|
|
tags: |
|
|
- generated_from_trainer |
|
|
metrics: |
|
|
- accuracy |
|
|
model-index: |
|
|
- name: phobert-base_v3 |
|
|
results: [] |
|
|
--- |
|
|
|
|
|
<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
|
|
should probably proofread and complete it, then remove this comment. --> |
|
|
|
|
|
# phobert-base_v3 |
|
|
|
|
|
This model is a fine-tuned version of [vinai/phobert-base](https://huggingface.co/vinai/phobert-base) on an unknown dataset. |
|
|
It achieves the following results on the evaluation set: |
|
|
- Loss: 1.2798 |
|
|
- Accuracy: 0.7805 |
|
|
- Precision Macro: 0.7813 |
|
|
- Recall Macro: 0.7807 |
|
|
- F1 Macro: 0.7806 |
|
|
- F1 Weighted: 0.7806 |
|
|
|
|
|
## 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: 128 |
|
|
- eval_batch_size: 128 |
|
|
- seed: 42 |
|
|
- gradient_accumulation_steps: 2 |
|
|
- total_train_batch_size: 256 |
|
|
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
|
|
- lr_scheduler_type: cosine |
|
|
- lr_scheduler_warmup_ratio: 0.1 |
|
|
- num_epochs: 20 |
|
|
- mixed_precision_training: Native AMP |
|
|
|
|
|
### Training results |
|
|
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision Macro | Recall Macro | F1 Macro | F1 Weighted | |
|
|
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------------:|:------------:|:--------:|:-----------:| |
|
|
| 1.0861 | 1.0 | 72 | 0.8945 | 0.5863 | 0.6024 | 0.5883 | 0.5734 | 0.5725 | |
|
|
| 0.8854 | 2.0 | 144 | 0.7401 | 0.6993 | 0.7354 | 0.6992 | 0.6982 | 0.6983 | |
|
|
| 0.5405 | 3.0 | 216 | 0.5891 | 0.7814 | 0.7817 | 0.7816 | 0.7813 | 0.7813 | |
|
|
| 0.4119 | 4.0 | 288 | 0.6523 | 0.7761 | 0.7776 | 0.7758 | 0.7760 | 0.7760 | |
|
|
| 0.2355 | 5.0 | 360 | 0.6712 | 0.7894 | 0.7899 | 0.7892 | 0.7894 | 0.7894 | |
|
|
| 0.1786 | 6.0 | 432 | 0.8116 | 0.7725 | 0.7733 | 0.7726 | 0.7726 | 0.7726 | |
|
|
| 0.1126 | 7.0 | 504 | 0.8907 | 0.7761 | 0.7792 | 0.7761 | 0.7761 | 0.7761 | |
|
|
| 0.0844 | 8.0 | 576 | 0.9184 | 0.7827 | 0.7834 | 0.7825 | 0.7826 | 0.7827 | |
|
|
| 0.0657 | 9.0 | 648 | 1.0276 | 0.7734 | 0.7769 | 0.7735 | 0.7737 | 0.7737 | |
|
|
| 0.0458 | 10.0 | 720 | 1.2265 | 0.7583 | 0.7713 | 0.7581 | 0.7582 | 0.7583 | |
|
|
| 0.0494 | 11.0 | 792 | 1.1001 | 0.7783 | 0.7793 | 0.7783 | 0.7784 | 0.7784 | |
|
|
| 0.0307 | 12.0 | 864 | 1.1487 | 0.7783 | 0.7798 | 0.7781 | 0.7783 | 0.7783 | |
|
|
| 0.0284 | 13.0 | 936 | 1.1877 | 0.7805 | 0.7812 | 0.7805 | 0.7805 | 0.7805 | |
|
|
| 0.0192 | 14.0 | 1008 | 1.2280 | 0.7836 | 0.7843 | 0.7839 | 0.7836 | 0.7836 | |
|
|
| 0.0172 | 15.0 | 1080 | 1.2466 | 0.7823 | 0.7823 | 0.7823 | 0.7823 | 0.7823 | |
|
|
| 0.0108 | 16.0 | 1152 | 1.2673 | 0.7809 | 0.7837 | 0.7810 | 0.7812 | 0.7812 | |
|
|
| 0.0111 | 17.0 | 1224 | 1.2614 | 0.7823 | 0.7825 | 0.7823 | 0.7823 | 0.7823 | |
|
|
| 0.0094 | 18.0 | 1296 | 1.2754 | 0.7814 | 0.7817 | 0.7815 | 0.7814 | 0.7815 | |
|
|
| 0.0079 | 19.0 | 1368 | 1.2823 | 0.7809 | 0.7821 | 0.7811 | 0.7811 | 0.7811 | |
|
|
| 0.0095 | 20.0 | 1440 | 1.2798 | 0.7805 | 0.7813 | 0.7807 | 0.7806 | 0.7806 | |
|
|
|
|
|
|
|
|
### Framework versions |
|
|
|
|
|
- Transformers 4.55.0 |
|
|
- Pytorch 2.7.0+cu126 |
|
|
- Datasets 4.0.0 |
|
|
- Tokenizers 0.21.4 |
|
|
|
