---
base_model: vinai/phobert-base-v2
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: PhoBERT-Final_Mixed-aug_insert_BERT
  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_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: 1.0553
- Accuracy: 0.72
- F1: 0.7149

## 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     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 0.924         | 1.0   | 88   | 0.7740          | 0.69     | 0.6809 |
| 0.6752        | 2.0   | 176  | 0.7030          | 0.68     | 0.6721 |
| 0.5014        | 3.0   | 264  | 0.7360          | 0.7      | 0.7000 |
| 0.3755        | 4.0   | 352  | 0.7763          | 0.75     | 0.7438 |
| 0.2593        | 5.0   | 440  | 0.8404          | 0.71     | 0.7065 |
| 0.2104        | 6.0   | 528  | 0.9165          | 0.71     | 0.7078 |
| 0.1361        | 7.0   | 616  | 1.0459          | 0.72     | 0.7149 |
| 0.1251        | 8.0   | 704  | 1.0553          | 0.72     | 0.7149 |


### Framework versions

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