---
base_model: vinai/phobert-base-v2
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
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# PhoBERT-cls-detail-in-Non_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: 0.2037
- Accuracy: 0.93
- F1: 0.9339

## 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     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 1.1155        | 1.0   | 25   | 0.9023          | 0.68     | 0.5898 |
| 0.725         | 2.0   | 50   | 0.4912          | 0.91     | 0.8689 |
| 0.4564        | 3.0   | 75   | 0.3118          | 0.92     | 0.8911 |
| 0.3084        | 4.0   | 100  | 0.2391          | 0.93     | 0.9339 |
| 0.2426        | 5.0   | 125  | 0.2064          | 0.93     | 0.9339 |
| 0.182         | 6.0   | 150  | 0.1888          | 0.96     | 0.96   |
| 0.1705        | 7.0   | 175  | 0.2049          | 0.93     | 0.9339 |
| 0.1599        | 8.0   | 200  | 0.2037          | 0.93     | 0.9339 |


### Framework versions

- Transformers 4.33.2
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3