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

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: 1.2677
- Accuracy: 0.7
- F1: 0.6952

## 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     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 0.9293        | 1.0   | 88   | 0.7964          | 0.67     | 0.6494 |
| 0.6574        | 2.0   | 176  | 0.7447          | 0.69     | 0.6842 |
| 0.4468        | 3.0   | 264  | 0.8170          | 0.7      | 0.6904 |
| 0.2964        | 4.0   | 352  | 0.8311          | 0.68     | 0.6751 |
| 0.1996        | 5.0   | 440  | 1.0457          | 0.7      | 0.6962 |
| 0.1475        | 6.0   | 528  | 1.1385          | 0.71     | 0.7026 |
| 0.0796        | 7.0   | 616  | 1.2282          | 0.7      | 0.6922 |
| 0.0785        | 8.0   | 704  | 1.2677          | 0.7      | 0.6952 |


### Framework versions

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