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: 0.5182
- Accuracy: 0.8713
- F1: 0.8710
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 |
|---|---|---|---|---|---|
| 0.5631 | 1.0 | 25 | 0.4327 | 0.8119 | 0.8105 |
| 0.3123 | 2.0 | 50 | 0.4440 | 0.8020 | 0.7971 |
| 0.1806 | 3.0 | 75 | 0.4117 | 0.8515 | 0.8518 |
| 0.1107 | 4.0 | 100 | 0.4446 | 0.8614 | 0.8607 |
| 0.0729 | 5.0 | 125 | 0.4965 | 0.8713 | 0.8710 |
| 0.0473 | 6.0 | 150 | 0.4914 | 0.8812 | 0.8799 |
| 0.049 | 7.0 | 175 | 0.5021 | 0.8713 | 0.8710 |
| 0.0255 | 8.0 | 200 | 0.5182 | 0.8713 | 0.8710 |
Framework versions
- Transformers 4.33.3
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3