---
base_model: vinai/phobert-base-v2
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: metadata-cls-no-gov-8k-vnnic
  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-no-gov-8k-vnnic

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: 0.2819
- Accuracy: 0.9319
- F1: 0.7796

## 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: 10

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:------:|:----:|:---------------:|:--------:|:------:|
| 0.5853        | 1.1364 | 150  | 0.2434          | 0.9311   | 0.7583 |
| 0.2425        | 2.2727 | 300  | 0.2510          | 0.9251   | 0.7630 |
| 0.1714        | 3.4091 | 450  | 0.2222          | 0.9345   | 0.7682 |
| 0.1274        | 4.5455 | 600  | 0.2391          | 0.9328   | 0.7862 |
| 0.1075        | 5.6818 | 750  | 0.2507          | 0.9319   | 0.7732 |
| 0.0867        | 6.8182 | 900  | 0.2808          | 0.9277   | 0.7711 |
| 0.0625        | 7.9545 | 1050 | 0.2965          | 0.9243   | 0.7674 |
| 0.0539        | 9.0909 | 1200 | 0.2819          | 0.9319   | 0.7796 |


### Framework versions

- Transformers 4.44.0
- Pytorch 2.1.2
- Datasets 2.20.0
- Tokenizers 0.19.1