---
base_model: vinai/phobert-base-v2
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: PhoBERT-Final_Mixed-aug_backtranslation-1
  results: []
---

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# PhoBERT-Final_Mixed-aug_backtranslation-1

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: 1.1895
- Accuracy: 0.71
- F1: 0.7168

## 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: 41
- 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     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 0.8611        | 1.0   | 86   | 0.6930          | 0.69     | 0.6660 |
| 0.5374        | 2.0   | 172  | 0.6692          | 0.72     | 0.7201 |
| 0.3615        | 3.0   | 258  | 0.7942          | 0.72     | 0.7249 |
| 0.2435        | 4.0   | 344  | 0.8958          | 0.71     | 0.7169 |
| 0.1793        | 5.0   | 430  | 1.0115          | 0.72     | 0.7256 |
| 0.153         | 6.0   | 516  | 1.0978          | 0.74     | 0.7410 |
| 0.1133        | 7.0   | 602  | 1.1828          | 0.68     | 0.6897 |
| 0.1031        | 8.0   | 688  | 1.1895          | 0.71     | 0.7168 |


### Framework versions

- Transformers 4.33.1
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3