---
base_model: vinai/phobert-base-v2
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: phobert_55k_bo_vn
  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_55k_bo_vn

This model is a fine-tuned version of [vinai/phobert-base-v2](https://huggingface.co/vinai/phobert-base-v2) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2688
- Accuracy: 0.9534
- F1: 0.9536

## 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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine_with_restarts
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|
| 0.211         | 1.0   | 1719  | 0.1383          | 0.9485   | 0.9487 |
| 0.1376        | 2.0   | 3438  | 0.1373          | 0.9521   | 0.9523 |
| 0.1105        | 3.0   | 5157  | 0.1431          | 0.9522   | 0.9527 |
| 0.0889        | 4.0   | 6876  | 0.1649          | 0.9534   | 0.9537 |
| 0.0715        | 5.0   | 8595  | 0.1770          | 0.9549   | 0.9548 |
| 0.0561        | 6.0   | 10314 | 0.1937          | 0.9533   | 0.9536 |
| 0.0443        | 7.0   | 12033 | 0.2260          | 0.9530   | 0.9533 |
| 0.0367        | 8.0   | 13752 | 0.2664          | 0.9529   | 0.9531 |
| 0.0327        | 9.0   | 15471 | 0.2663          | 0.9532   | 0.9534 |
| 0.0298        | 10.0  | 17190 | 0.2688          | 0.9534   | 0.9536 |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.1.2
- Datasets 2.19.1
- Tokenizers 0.19.1