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

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# PhoBERT-cls-detail-in-Non_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: 0.2965
- Accuracy: 0.95
- F1: 0.9359

## 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     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 1.5312        | 1.0   | 25   | 1.2681          | 0.55     | 0.4060 |
| 1.1478        | 2.0   | 50   | 0.8709          | 0.82     | 0.7465 |
| 0.7779        | 3.0   | 75   | 0.5259          | 0.92     | 0.8928 |
| 0.528         | 4.0   | 100  | 0.3918          | 0.92     | 0.8928 |
| 0.4236        | 5.0   | 125  | 0.3363          | 0.94     | 0.9254 |
| 0.3641        | 6.0   | 150  | 0.3035          | 0.95     | 0.9359 |
| 0.3356        | 7.0   | 175  | 0.2965          | 0.95     | 0.9359 |


### Framework versions

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