---
library_name: transformers
license: agpl-3.0
base_model: vinai/phobert-base-v2
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: metadata-cls_15_10
  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. -->

# metadata-cls_15_10

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: 0.0128
- Accuracy: 0.9967
- F1: 0.9932

## 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: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-------:|:----:|:---------------:|:--------:|:------:|
| 0.5273        | 1.0067  | 150  | 0.2313          | 0.9384   | 0.8468 |
| 0.2312        | 2.0134  | 300  | 0.1456          | 0.9581   | 0.9182 |
| 0.1542        | 3.0201  | 450  | 0.0944          | 0.9747   | 0.9471 |
| 0.1199        | 4.0268  | 600  | 0.0747          | 0.9810   | 0.9600 |
| 0.0943        | 5.0336  | 750  | 0.0640          | 0.9827   | 0.9608 |
| 0.0837        | 6.0403  | 900  | 0.0458          | 0.9894   | 0.9748 |
| 0.0645        | 7.0470  | 1050 | 0.0435          | 0.9894   | 0.9767 |
| 0.0509        | 8.0537  | 1200 | 0.0313          | 0.9925   | 0.9819 |
| 0.043         | 9.0604  | 1350 | 0.0242          | 0.9944   | 0.9859 |
| 0.0345        | 10.0671 | 1500 | 0.0196          | 0.9954   | 0.9904 |
| 0.03          | 11.0738 | 1650 | 0.0179          | 0.9956   | 0.9913 |
| 0.0231        | 12.0805 | 1800 | 0.0162          | 0.9958   | 0.9914 |
| 0.0227        | 13.0872 | 1950 | 0.0137          | 0.9966   | 0.9930 |
| 0.0181        | 14.0940 | 2100 | 0.0128          | 0.9967   | 0.9932 |


### Framework versions

- Transformers 4.45.2
- Pytorch 2.1.2
- Datasets 2.20.0
- Tokenizers 0.20.1