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