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---
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 |