---
base_model: vinai/phobert-base-v2
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: model
  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. -->

# model

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: 0.1373
- Accuracy: 0.9709

## 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: 5e-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: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 95   | 1.0978          | 0.8201   |
| No log        | 2.0   | 190  | 0.5250          | 0.9392   |
| No log        | 3.0   | 285  | 0.3076          | 0.9418   |
| No log        | 4.0   | 380  | 0.2149          | 0.9471   |
| No log        | 5.0   | 475  | 0.2237          | 0.9497   |
| 0.6823        | 6.0   | 570  | 0.1904          | 0.9630   |
| 0.6823        | 7.0   | 665  | 0.1716          | 0.9656   |
| 0.6823        | 8.0   | 760  | 0.1373          | 0.9709   |
| 0.6823        | 9.0   | 855  | 0.1403          | 0.9683   |
| 0.6823        | 10.0  | 950  | 0.1374          | 0.9709   |


### Framework versions

- Transformers 4.36.1
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0