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finetuned-WangchanBERTa-TSCC-property

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SirawitC/finetuned-WangchanBERTa-TSCC-property

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  1. README.md +86 -2
  2. model.safetensors +1 -1
  3. runs/Sep10_06-57-24_b76d5ad020a6/events.out.tfevents.1725951451.b76d5ad020a6.586.0 +3 -0
  4. runs/Sep10_06-57-24_b76d5ad020a6/events.out.tfevents.1725951769.b76d5ad020a6.586.1 +3 -0
  5. runs/Sep10_07-11-34_b76d5ad020a6/events.out.tfevents.1725952298.b76d5ad020a6.4887.0 +3 -0
  6. runs/Sep10_07-11-34_b76d5ad020a6/events.out.tfevents.1725952706.b76d5ad020a6.4887.1 +3 -0
  7. training_args.bin +2 -2
README.md CHANGED
@@ -17,8 +17,8 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [airesearch/wangchanberta-base-att-spm-uncased](https://huggingface.co/airesearch/wangchanberta-base-att-spm-uncased) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.5108
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- - Accuracy: 0.9390
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  ## Model description
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@@ -47,6 +47,90 @@ The following hyperparameters were used during training:
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  ### Training results
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  ### Framework versions
 
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  This model is a fine-tuned version of [airesearch/wangchanberta-base-att-spm-uncased](https://huggingface.co/airesearch/wangchanberta-base-att-spm-uncased) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.2288
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+ - Accuracy: 0.9634
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  ## Model description
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  ### Training results
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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+ |:-------------:|:------:|:----:|:---------------:|:--------:|
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+ | 0.6835 | 0.1220 | 10 | 0.6029 | 0.6585 |
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+ | 0.5255 | 0.2439 | 20 | 0.7177 | 0.6707 |
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+ | 0.3303 | 0.3659 | 30 | 0.3454 | 0.8537 |
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+ | 0.3471 | 0.4878 | 40 | 0.3404 | 0.8902 |
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+ | 0.2569 | 0.6098 | 50 | 0.2818 | 0.9146 |
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+ | 0.1546 | 0.7317 | 60 | 0.1566 | 0.9512 |
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+ | 0.1234 | 0.8537 | 70 | 0.0562 | 0.9756 |
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+ | 0.2935 | 0.9756 | 80 | 0.2113 | 0.9512 |
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+ | 0.0292 | 1.0976 | 90 | 0.1369 | 0.9512 |
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+ | 0.1396 | 1.2195 | 100 | 0.2530 | 0.9512 |
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+ | 0.0867 | 1.3415 | 110 | 0.1326 | 0.9512 |
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+ | 0.059 | 1.4634 | 120 | 0.0811 | 0.9512 |
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+ | 0.0024 | 1.5854 | 130 | 0.3948 | 0.9512 |
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+ | 0.2261 | 1.7073 | 140 | 0.2322 | 0.9268 |
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+ | 0.0986 | 1.8293 | 150 | 0.3132 | 0.9390 |
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+ | 0.0819 | 1.9512 | 160 | 0.2300 | 0.9390 |
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+ | 0.0149 | 2.0732 | 170 | 0.2773 | 0.9268 |
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+ | 0.0151 | 2.1951 | 180 | 0.2996 | 0.9268 |
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+ | 0.001 | 2.3171 | 190 | 0.1910 | 0.9390 |
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+ | 0.0005 | 2.4390 | 200 | 0.2285 | 0.9268 |
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+ | 0.0379 | 2.5610 | 210 | 0.3384 | 0.9390 |
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+ | 0.0013 | 2.6829 | 220 | 0.1087 | 0.9756 |
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+ | 0.0002 | 2.8049 | 230 | 0.1113 | 0.9756 |
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+ | 0.0901 | 2.9268 | 240 | 0.1219 | 0.9756 |
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+ | 0.0537 | 3.0488 | 250 | 0.2109 | 0.9512 |
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+ | 0.0004 | 3.1707 | 260 | 0.1496 | 0.9756 |
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+ | 0.0012 | 3.2927 | 270 | 0.1627 | 0.9634 |
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+ | 0.0107 | 3.4146 | 280 | 0.1552 | 0.9634 |
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+ | 0.019 | 3.5366 | 290 | 0.1547 | 0.9634 |
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+ | 0.0003 | 3.6585 | 300 | 0.1568 | 0.9634 |
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+ | 0.0003 | 3.7805 | 310 | 0.1596 | 0.9634 |
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+ | 0.0002 | 3.9024 | 320 | 0.2054 | 0.9634 |
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+ | 0.0004 | 4.0244 | 330 | 0.3416 | 0.9268 |
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+ | 0.0002 | 4.1463 | 340 | 0.4531 | 0.9390 |
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+ | 0.0002 | 4.2683 | 350 | 0.4530 | 0.9390 |
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+ | 0.0002 | 4.3902 | 360 | 0.4035 | 0.9268 |
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+ | 0.0005 | 4.5122 | 370 | 0.3358 | 0.9268 |
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+ | 0.0002 | 4.6341 | 380 | 0.2717 | 0.9390 |
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+ | 0.0001 | 4.7561 | 390 | 0.2437 | 0.9512 |
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+ | 0.0031 | 4.8780 | 400 | 0.2317 | 0.9634 |
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+ | 0.0001 | 5.0 | 410 | 0.2259 | 0.9634 |
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+ | 0.0001 | 5.1220 | 420 | 0.2159 | 0.9634 |
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+ | 0.0001 | 5.2439 | 430 | 0.2098 | 0.9634 |
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+ | 0.0001 | 5.3659 | 440 | 0.2432 | 0.9512 |
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+ | 0.0001 | 5.4878 | 450 | 0.2555 | 0.9512 |
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+ | 0.0001 | 5.6098 | 460 | 0.2576 | 0.9512 |
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+ | 0.0001 | 5.7317 | 470 | 0.2557 | 0.9512 |
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+ | 0.0364 | 5.8537 | 480 | 0.2550 | 0.9512 |
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+ | 0.0001 | 5.9756 | 490 | 0.2543 | 0.9512 |
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+ | 0.0001 | 6.0976 | 500 | 0.2516 | 0.9512 |
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+ | 0.0001 | 6.2195 | 510 | 0.2487 | 0.9512 |
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+ | 0.0001 | 6.3415 | 520 | 0.2484 | 0.9512 |
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+ | 0.0001 | 6.4634 | 530 | 0.2082 | 0.9634 |
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+ | 0.0001 | 6.5854 | 540 | 0.1980 | 0.9634 |
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+ | 0.0007 | 6.7073 | 550 | 0.1934 | 0.9634 |
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+ | 0.0001 | 6.8293 | 560 | 0.1916 | 0.9634 |
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+ | 0.0001 | 6.9512 | 570 | 0.1900 | 0.9634 |
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+ | 0.0066 | 7.0732 | 580 | 0.1863 | 0.9634 |
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+ | 0.0001 | 7.1951 | 590 | 0.1829 | 0.9634 |
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+ | 0.0001 | 7.3171 | 600 | 0.1856 | 0.9634 |
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+ | 0.0013 | 7.4390 | 610 | 0.1972 | 0.9634 |
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+ | 0.0001 | 7.5610 | 620 | 0.2031 | 0.9634 |
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+ | 0.0 | 7.6829 | 630 | 0.2052 | 0.9634 |
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+ | 0.0008 | 7.8049 | 640 | 0.2082 | 0.9634 |
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+ | 0.001 | 7.9268 | 650 | 0.2091 | 0.9634 |
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+ | 0.0001 | 8.0488 | 660 | 0.2103 | 0.9634 |
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+ | 0.0001 | 8.1707 | 670 | 0.2098 | 0.9634 |
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+ | 0.0 | 8.2927 | 680 | 0.2103 | 0.9634 |
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+ | 0.0001 | 8.4146 | 690 | 0.2109 | 0.9634 |
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+ | 0.0001 | 8.5366 | 700 | 0.2239 | 0.9634 |
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+ | 0.0 | 8.6585 | 710 | 0.2281 | 0.9634 |
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+ | 0.0 | 8.7805 | 720 | 0.2294 | 0.9634 |
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+ | 0.0 | 8.9024 | 730 | 0.2296 | 0.9634 |
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+ | 0.0003 | 9.0244 | 740 | 0.2300 | 0.9634 |
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+ | 0.0001 | 9.1463 | 750 | 0.2301 | 0.9634 |
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+ | 0.0001 | 9.2683 | 760 | 0.2294 | 0.9634 |
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+ | 0.0001 | 9.3902 | 770 | 0.2290 | 0.9634 |
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+ | 0.0 | 9.5122 | 780 | 0.2290 | 0.9634 |
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+ | 0.0001 | 9.6341 | 790 | 0.2288 | 0.9634 |
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+ | 0.0001 | 9.7561 | 800 | 0.2288 | 0.9634 |
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+ | 0.0 | 9.8780 | 810 | 0.2288 | 0.9634 |
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+ | 0.0001 | 10.0 | 820 | 0.2288 | 0.9634 |
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  ### Framework versions
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