---
base_model: vinai/phobert-base-v2
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: PhoBERT-Final_Mixed-aug_swap
  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-Final_Mixed-aug_swap

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: 1.3287
- Accuracy: 0.69
- F1: 0.6820

## 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     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 0.9179        | 1.0   | 87   | 0.7611          | 0.67     | 0.6462 |
| 0.5989        | 2.0   | 174  | 0.8002          | 0.66     | 0.6464 |
| 0.3757        | 3.0   | 261  | 0.7484          | 0.72     | 0.7110 |
| 0.2615        | 4.0   | 348  | 0.9061          | 0.7      | 0.6977 |
| 0.1511        | 5.0   | 435  | 1.0824          | 0.68     | 0.6706 |
| 0.099         | 6.0   | 522  | 1.1667          | 0.7      | 0.7000 |
| 0.0873        | 7.0   | 609  | 1.3050          | 0.7      | 0.6932 |
| 0.0553        | 8.0   | 696  | 1.3287          | 0.69     | 0.6820 |


### Framework versions

- Transformers 4.32.1
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3