metadata
base_model: vinai/phobert-base-v2
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: PhoBERT-cls-OCR
results: []
PhoBERT-cls-OCR
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: 0.6475
- Accuracy: 0.8416
- F1: 0.8422
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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 0.5849 | 1.0 | 25 | 0.4385 | 0.8218 | 0.8225 |
| 0.3382 | 2.0 | 50 | 0.3785 | 0.8614 | 0.8599 |
| 0.1897 | 3.0 | 75 | 0.4339 | 0.8515 | 0.8511 |
| 0.1101 | 4.0 | 100 | 0.4626 | 0.8614 | 0.8599 |
| 0.0798 | 5.0 | 125 | 0.5006 | 0.8713 | 0.8703 |
| 0.0547 | 6.0 | 150 | 0.5670 | 0.8614 | 0.8614 |
| 0.034 | 7.0 | 175 | 0.5568 | 0.8812 | 0.8806 |
| 0.0121 | 8.0 | 200 | 0.6414 | 0.8317 | 0.8326 |
| 0.0207 | 9.0 | 225 | 0.6713 | 0.8416 | 0.8427 |
| 0.0203 | 10.0 | 250 | 0.6475 | 0.8416 | 0.8422 |
Framework versions
- Transformers 4.34.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.14.1