---
base_model: vinai/phobert-base
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: PhoBERT-cls-OCR
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# PhoBERT-cls-OCR

This model is a fine-tuned version of [vinai/phobert-base](https://huggingface.co/vinai/phobert-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4288
- Accuracy: 0.8812
- F1: 0.8812

## 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: 7

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 0.5728        | 1.0   | 25   | 0.4112          | 0.8614   | 0.8590 |
| 0.2892        | 2.0   | 50   | 0.3444          | 0.8515   | 0.8511 |
| 0.1954        | 3.0   | 75   | 0.3638          | 0.8812   | 0.8816 |
| 0.1387        | 4.0   | 100  | 0.3591          | 0.8812   | 0.8806 |
| 0.1029        | 5.0   | 125  | 0.3809          | 0.8911   | 0.8908 |
| 0.053         | 6.0   | 150  | 0.4145          | 0.8911   | 0.8903 |
| 0.0527        | 7.0   | 175  | 0.4288          | 0.8812   | 0.8812 |


### Framework versions

- Transformers 4.34.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.14.1