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---
base_model: vinai/phobert-base-v2
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: metadata-cls-no-gov-8k-v2
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. -->
[<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/s6iy3mkr)
# metadata-cls-no-gov-8k-v2
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: 0.3052
- Accuracy: 0.9447
- F1: 0.7927
## 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 |
|:-------------:|:-------:|:----:|:---------------:|:--------:|:------:|
| 0.5649 | 1.6260 | 200 | 0.2215 | 0.9455 | 0.7479 |
| 0.1634 | 3.2520 | 400 | 0.1869 | 0.9438 | 0.8204 |
| 0.1222 | 4.8780 | 600 | 0.2286 | 0.9370 | 0.7837 |
| 0.0808 | 6.5041 | 800 | 0.2174 | 0.9532 | 0.8263 |
| 0.0528 | 8.1301 | 1000 | 0.2440 | 0.9387 | 0.7862 |
| 0.046 | 9.7561 | 1200 | 0.2416 | 0.9472 | 0.8180 |
| 0.0329 | 11.3821 | 1400 | 0.2631 | 0.9464 | 0.7967 |
| 0.0271 | 13.0081 | 1600 | 0.2769 | 0.9481 | 0.8124 |
| 0.0179 | 14.6341 | 1800 | 0.2687 | 0.9506 | 0.8122 |
| 0.0185 | 16.2602 | 2000 | 0.2935 | 0.9438 | 0.7921 |
| 0.0153 | 17.8862 | 2200 | 0.2957 | 0.9455 | 0.7907 |
| 0.0146 | 19.5122 | 2400 | 0.3052 | 0.9447 | 0.7927 |
### Framework versions
- Transformers 4.42.4
- Pytorch 2.1.2
- Datasets 2.20.0
- Tokenizers 0.19.1
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