---
base_model: vinai/phobert-base-v2
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: PhoBERT-Final_Mixed-train-1
  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-train-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: 0.8720
- Accuracy: 0.71
- F1: 0.7085

## 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     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 1.0125        | 1.0   | 44   | 0.8552          | 0.63     | 0.5142 |
| 0.7443        | 2.0   | 88   | 0.6888          | 0.7      | 0.6941 |
| 0.5851        | 3.0   | 132  | 0.6873          | 0.72     | 0.7164 |
| 0.4457        | 4.0   | 176  | 0.7423          | 0.7      | 0.7021 |
| 0.374         | 5.0   | 220  | 0.7960          | 0.71     | 0.7019 |
| 0.2885        | 6.0   | 264  | 0.8073          | 0.7      | 0.7016 |
| 0.2711        | 7.0   | 308  | 0.8329          | 0.71     | 0.7088 |
| 0.2317        | 8.0   | 352  | 0.8720          | 0.71     | 0.7085 |


### Framework versions

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