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

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# PhoBERT-train-aug_insert_BERT

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: 1.1962
- Accuracy: 0.72
- F1: 0.7303

## 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     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 0.8879        | 1.0   | 87   | 0.7145          | 0.68     | 0.6453 |
| 0.586         | 2.0   | 174  | 0.6479          | 0.72     | 0.7265 |
| 0.3982        | 3.0   | 261  | 0.7353          | 0.72     | 0.7292 |
| 0.2815        | 4.0   | 348  | 0.8297          | 0.71     | 0.7152 |
| 0.2042        | 5.0   | 435  | 0.9852          | 0.71     | 0.7197 |
| 0.1438        | 6.0   | 522  | 1.0917          | 0.71     | 0.7198 |
| 0.1327        | 7.0   | 609  | 1.1657          | 0.72     | 0.7303 |
| 0.1016        | 8.0   | 696  | 1.1962          | 0.72     | 0.7303 |


### Framework versions

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