metadata
library_name: transformers
license: agpl-3.0
base_model: vinai/phobert-base-v2
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: PhoBert_Lexical_CITA
results: []
PhoBert_Lexical_CITA
This model is a fine-tuned version of vinai/phobert-base-v2 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.6736
- Accuracy: 0.783
- F1: 0.7825
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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 0.5393 | 1.0 | 250 | 0.4700 | 0.7695 | 0.7680 |
| 0.4508 | 2.0 | 500 | 0.4686 | 0.7735 | 0.7735 |
| 0.3951 | 3.0 | 750 | 0.4711 | 0.78 | 0.7800 |
| 0.3402 | 4.0 | 1000 | 0.4895 | 0.7845 | 0.7846 |
| 0.2947 | 5.0 | 1250 | 0.5293 | 0.782 | 0.7815 |
| 0.2516 | 6.0 | 1500 | 0.5567 | 0.7775 | 0.7773 |
| 0.2199 | 7.0 | 1750 | 0.5993 | 0.787 | 0.7857 |
| 0.192 | 8.0 | 2000 | 0.6361 | 0.7825 | 0.7816 |
| 0.1705 | 9.0 | 2250 | 0.6498 | 0.7835 | 0.7834 |
| 0.1526 | 10.0 | 2500 | 0.6736 | 0.783 | 0.7825 |
Framework versions
- Transformers 4.48.0
- Pytorch 2.1.2
- Datasets 2.20.0
- Tokenizers 0.21.0