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---
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
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