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---
library_name: transformers
base_model: monsoon-nlp/bert-base-thai
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: bert-base-thai-intent-booking
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. -->
# bert-base-thai-intent-booking
This model is a fine-tuned version of [monsoon-nlp/bert-base-thai](https://huggingface.co/monsoon-nlp/bert-base-thai) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.1511
- Accuracy: 0.1937
- F1: 0.1641
- Precision: 0.2236
- Recall: 0.1937
## 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: 5e-05
- train_batch_size: 16
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 64
- num_epochs: 20
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 2.368 | 1.0 | 65 | 2.3624 | 0.0901 | 0.0149 | 0.0081 | 0.0901 |
| 2.3586 | 2.0 | 130 | 2.2374 | 0.1577 | 0.0963 | 0.1107 | 0.1577 |
| 2.2987 | 3.0 | 195 | 2.2589 | 0.1216 | 0.0626 | 0.0890 | 0.1216 |
| 2.279 | 4.0 | 260 | 2.1771 | 0.1757 | 0.1329 | 0.2163 | 0.1757 |
| 2.2326 | 5.0 | 325 | 2.2099 | 0.2027 | 0.1548 | 0.1497 | 0.2027 |
| 2.2273 | 6.0 | 390 | 2.1809 | 0.1712 | 0.1245 | 0.1127 | 0.1712 |
| 2.2303 | 7.0 | 455 | 2.2168 | 0.1486 | 0.1030 | 0.1190 | 0.1486 |
| 2.196 | 8.0 | 520 | 2.1862 | 0.1937 | 0.1478 | 0.1615 | 0.1937 |
| 2.1848 | 9.0 | 585 | 2.1320 | 0.2162 | 0.1773 | 0.2192 | 0.2162 |
| 2.183 | 10.0 | 650 | 2.1771 | 0.1712 | 0.1240 | 0.1703 | 0.1712 |
| 2.1669 | 11.0 | 715 | 2.1672 | 0.2117 | 0.1849 | 0.2453 | 0.2117 |
| 2.1586 | 12.0 | 780 | 2.1237 | 0.2162 | 0.1939 | 0.3552 | 0.2162 |
| 2.1465 | 13.0 | 845 | 2.1269 | 0.2117 | 0.1834 | 0.2440 | 0.2117 |
| 2.1454 | 14.0 | 910 | 2.1160 | 0.2162 | 0.1939 | 0.3552 | 0.2162 |
| 2.1404 | 15.0 | 975 | 2.1089 | 0.2162 | 0.1936 | 0.3561 | 0.2162 |
| 2.1293 | 16.0 | 1040 | 2.1272 | 0.2162 | 0.1947 | 0.3584 | 0.2162 |
| 2.1193 | 17.0 | 1105 | 2.1043 | 0.2117 | 0.1836 | 0.2431 | 0.2117 |
| 2.1094 | 18.0 | 1170 | 2.1053 | 0.2117 | 0.1895 | 0.2977 | 0.2117 |
| 2.1063 | 19.0 | 1235 | 2.1055 | 0.2117 | 0.1901 | 0.2989 | 0.2117 |
| 2.0888 | 20.0 | 1300 | 2.1067 | 0.2117 | 0.1895 | 0.2977 | 0.2117 |
### Framework versions
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.19.1
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