---
base_model: gechim/metadata-cls-no-gov-8k-v3
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: PhobertLexicalMeta
  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/h3pap4wy)
# PhobertLexicalMeta

This model is a fine-tuned version of [gechim/metadata-cls-no-gov-8k-v3](https://huggingface.co/gechim/metadata-cls-no-gov-8k-v3) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0927
- Accuracy: 0.9792
- F1: 0.9664

## 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     |
|:-------------:|:------:|:----:|:---------------:|:--------:|:------:|
| 0.1701        | 1.9608 | 200  | 0.0936          | 0.9741   | 0.9575 |
| 0.0537        | 3.9216 | 400  | 0.0780          | 0.9780   | 0.9647 |
| 0.0252        | 5.8824 | 600  | 0.0762          | 0.9805   | 0.9687 |
| 0.016         | 7.8431 | 800  | 0.0996          | 0.9780   | 0.9640 |
| 0.0098        | 9.8039 | 1000 | 0.0927          | 0.9792   | 0.9664 |


### Framework versions

- Transformers 4.43.1
- Pytorch 2.1.2
- Datasets 2.20.0
- Tokenizers 0.19.1