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: 0.1546
- Accuracy: 0.9593
- F1: 0.9592
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: 8
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 0.4221 | 1.0 | 43 | 0.2568 | 0.9070 | 0.9049 |
| 0.1993 | 2.0 | 86 | 0.1515 | 0.9593 | 0.9592 |
| 0.1313 | 3.0 | 129 | 0.1582 | 0.9593 | 0.9591 |
| 0.0966 | 4.0 | 172 | 0.1456 | 0.9651 | 0.9651 |
| 0.0737 | 5.0 | 215 | 0.1432 | 0.9651 | 0.9651 |
| 0.0592 | 6.0 | 258 | 0.1488 | 0.9651 | 0.9651 |
| 0.0633 | 7.0 | 301 | 0.1605 | 0.9593 | 0.9592 |
| 0.0575 | 8.0 | 344 | 0.1546 | 0.9593 | 0.9592 |
Framework versions
- Transformers 4.33.1
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3