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

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# PhoBERT-Final_Mixed-aug_insert_tfidf

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: 1.2673
- Accuracy: 0.73
- F1: 0.7262

## 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     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 0.894         | 1.0   | 88   | 0.7277          | 0.66     | 0.6187 |
| 0.5738        | 2.0   | 176  | 0.7561          | 0.7      | 0.6957 |
| 0.3647        | 3.0   | 264  | 0.8054          | 0.72     | 0.7149 |
| 0.2496        | 4.0   | 352  | 1.0288          | 0.69     | 0.6842 |
| 0.1633        | 5.0   | 440  | 1.1435          | 0.7      | 0.6943 |
| 0.1162        | 6.0   | 528  | 1.1985          | 0.72     | 0.7157 |
| 0.0909        | 7.0   | 616  | 1.2491          | 0.73     | 0.7262 |
| 0.0722        | 8.0   | 704  | 1.2673          | 0.73     | 0.7262 |


### Framework versions

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