|
--- |
|
base_model: clicknext/phayathaibert |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- precision |
|
- recall |
|
- f1 |
|
- accuracy |
|
model-index: |
|
- name: phayathaibert-thainer |
|
results: [] |
|
widget: |
|
- text: >- |
|
ประเทศไทยอยู่ในทวีปเอเชีย |
|
example_title: test_example_1 |
|
- text: ไทยอยู่ในเจอ |
|
example_title: test_example_2 |
|
license: mit |
|
language: |
|
- th |
|
library_name: transformers |
|
pipeline_tag: token-classification |
|
datasets: |
|
- pythainlp/thainer-corpus-v2 |
|
--- |
|
|
|
<!-- 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. --> |
|
|
|
# phayathaibert-thainer |
|
|
|
This model is a fine-tuned version of [clicknext/phayathaibert](https://huggingface.co/clicknext/phayathaibert) on an unknown dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.1324 |
|
- Precision: 0.8432 |
|
- Recall: 0.8915 |
|
- F1: 0.8666 |
|
- Accuracy: 0.9735 |
|
|
|
## 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: 8 |
|
- eval_batch_size: 8 |
|
- seed: 42 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- num_epochs: 10 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |
|
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| |
|
| No log | 1.0 | 493 | 0.1401 | 0.7300 | 0.7941 | 0.7607 | 0.9607 | |
|
| 0.3499 | 2.0 | 986 | 0.1201 | 0.7863 | 0.8464 | 0.8152 | 0.9688 | |
|
| 0.0961 | 3.0 | 1479 | 0.1169 | 0.8050 | 0.8663 | 0.8345 | 0.9715 | |
|
| 0.0617 | 4.0 | 1972 | 0.1137 | 0.8155 | 0.8656 | 0.8398 | 0.9718 | |
|
| 0.0438 | 5.0 | 2465 | 0.1280 | 0.8201 | 0.8714 | 0.8450 | 0.9725 | |
|
| 0.0302 | 6.0 | 2958 | 0.1386 | 0.8266 | 0.8730 | 0.8492 | 0.9726 | |
|
| 0.0239 | 7.0 | 3451 | 0.1401 | 0.8353 | 0.8789 | 0.8565 | 0.9733 | |
|
| 0.0166 | 8.0 | 3944 | 0.1444 | 0.8356 | 0.8782 | 0.8564 | 0.9738 | |
|
| 0.0139 | 9.0 | 4437 | 0.1530 | 0.8341 | 0.8785 | 0.8557 | 0.9735 | |
|
| 0.0106 | 10.0 | 4930 | 0.1508 | 0.8394 | 0.8782 | 0.8583 | 0.9738 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.35.2 |
|
- Pytorch 2.1.0+cu118 |
|
- Datasets 2.15.0 |
|
- Tokenizers 0.15.0 |
