---
base_model: vinai/phobert-base-v2
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: metadata-cls-gemini
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/nguyenducbao/huggingface/runs/08pk0u8k)
# metadata-cls-gemini

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: 1.0111
- Accuracy: 0.8183
- F1: 0.7722

## 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: 20

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-------:|:----:|:---------------:|:--------:|:------:|
| 0.9411        | 1.6949  | 200  | 0.5887          | 0.8002   | 0.6394 |
| 0.4312        | 3.3898  | 400  | 0.5675          | 0.8097   | 0.7790 |
| 0.2745        | 5.0847  | 600  | 0.5685          | 0.8164   | 0.7767 |
| 0.2199        | 6.7797  | 800  | 0.6602          | 0.8116   | 0.7998 |
| 0.1536        | 8.4746  | 1000 | 0.8254          | 0.8069   | 0.7707 |
| 0.1021        | 10.1695 | 1200 | 0.8674          | 0.8097   | 0.7889 |
| 0.0928        | 11.8644 | 1400 | 0.8696          | 0.8145   | 0.7789 |
| 0.0692        | 13.5593 | 1600 | 0.9211          | 0.8259   | 0.7926 |
| 0.049         | 15.2542 | 1800 | 0.9573          | 0.8221   | 0.7899 |
| 0.0391        | 16.9492 | 2000 | 1.0388          | 0.8154   | 0.7713 |
| 0.0372        | 18.6441 | 2200 | 1.0111          | 0.8183   | 0.7722 |


### Framework versions

- Transformers 4.42.4
- Pytorch 2.1.2
- Datasets 2.20.0
- Tokenizers 0.19.1