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

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# PhoBERT-Final_Mixed-aug_insert_BERT-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: 1.1594
- Accuracy: 0.72
- F1: 0.7195

## 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     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 0.9312        | 1.0   | 88   | 0.7278          | 0.68     | 0.6701 |
| 0.6476        | 2.0   | 176  | 0.7024          | 0.71     | 0.7039 |
| 0.4815        | 3.0   | 264  | 0.7657          | 0.7      | 0.6959 |
| 0.341         | 4.0   | 352  | 0.8302          | 0.7      | 0.6994 |
| 0.2368        | 5.0   | 440  | 0.8699          | 0.72     | 0.7229 |
| 0.1705        | 6.0   | 528  | 1.0489          | 0.71     | 0.7094 |
| 0.1169        | 7.0   | 616  | 1.1685          | 0.71     | 0.7094 |
| 0.1176        | 8.0   | 704  | 1.1594          | 0.72     | 0.7195 |


### Framework versions

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