---
base_model: vinai/phobert-base-v2
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-v2](https://huggingface.co/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