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fine-tuned-DatasetQAS-IDK-MRC-with-indobert-base-uncased-with-ITTL-without-freeze-LR-1e-05

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update model card README.md

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@@ -16,9 +16,9 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [indolem/indobert-base-uncased](https://huggingface.co/indolem/indobert-base-uncased) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 1.0860
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- - Exact Match: 64.7906
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- - F1: 70.2020
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  ## Model description
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@@ -51,26 +51,26 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Exact Match | F1 |
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  |:-------------:|:-----:|:----:|:---------------:|:-----------:|:-------:|
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- | 6.2255 | 0.49 | 36 | 2.4921 | 50.0 | 50.0 |
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- | 3.6958 | 0.98 | 72 | 1.9696 | 49.6073 | 49.8277 |
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- | 2.2068 | 1.48 | 108 | 1.8415 | 47.3822 | 48.9302 |
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- | 2.2068 | 1.97 | 144 | 1.7148 | 48.1675 | 51.1818 |
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- | 1.9768 | 2.46 | 180 | 1.5553 | 51.8325 | 56.0847 |
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- | 1.7318 | 2.95 | 216 | 1.4373 | 55.1047 | 59.8473 |
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- | 1.5469 | 3.45 | 252 | 1.2970 | 58.3770 | 63.3911 |
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- | 1.5469 | 3.94 | 288 | 1.2882 | 58.9005 | 64.0631 |
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- | 1.3771 | 4.44 | 324 | 1.2048 | 62.0419 | 66.6696 |
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- | 1.2296 | 4.93 | 360 | 1.1860 | 61.7801 | 66.8504 |
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- | 1.2296 | 5.42 | 396 | 1.1807 | 60.3403 | 65.5550 |
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- | 1.1715 | 5.91 | 432 | 1.1330 | 62.6963 | 67.5995 |
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- | 1.0833 | 6.41 | 468 | 1.1292 | 62.8272 | 67.7732 |
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- | 1.025 | 6.9 | 504 | 1.1256 | 63.3508 | 68.7945 |
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- | 1.025 | 7.4 | 540 | 1.0740 | 64.5288 | 69.8302 |
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- | 1.0033 | 7.89 | 576 | 1.0828 | 64.5288 | 69.8559 |
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- | 0.9603 | 8.38 | 612 | 1.0870 | 63.7435 | 69.1867 |
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- | 0.9603 | 8.87 | 648 | 1.0655 | 65.9686 | 70.8956 |
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- | 0.94 | 9.37 | 684 | 1.0717 | 65.3141 | 70.5016 |
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- | 0.9259 | 9.86 | 720 | 1.0860 | 64.7906 | 70.2020 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [indolem/indobert-base-uncased](https://huggingface.co/indolem/indobert-base-uncased) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 1.0942
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+ - Exact Match: 64.3979
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+ - F1: 69.8535
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Exact Match | F1 |
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  |:-------------:|:-----:|:----:|:---------------:|:-----------:|:-------:|
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+ | 6.1478 | 0.49 | 36 | 2.4099 | 49.8691 | 49.8691 |
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+ | 3.581 | 0.98 | 72 | 1.9550 | 49.8691 | 49.8691 |
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+ | 2.195 | 1.48 | 108 | 1.8446 | 49.3455 | 49.8564 |
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+ | 2.195 | 1.97 | 144 | 1.7512 | 49.4764 | 51.2613 |
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+ | 2.0071 | 2.46 | 180 | 1.6324 | 49.6073 | 52.3994 |
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+ | 1.8105 | 2.95 | 216 | 1.5278 | 52.7487 | 55.8533 |
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+ | 1.6668 | 3.45 | 252 | 1.3938 | 56.6754 | 60.5142 |
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+ | 1.6668 | 3.94 | 288 | 1.3243 | 56.9372 | 62.8755 |
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+ | 1.4715 | 4.44 | 324 | 1.2475 | 60.6021 | 66.5376 |
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+ | 1.3112 | 4.93 | 360 | 1.2257 | 59.4241 | 65.0059 |
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+ | 1.3112 | 5.42 | 396 | 1.1793 | 60.9948 | 66.2895 |
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+ | 1.2443 | 5.91 | 432 | 1.1485 | 63.4817 | 69.0854 |
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+ | 1.1586 | 6.41 | 468 | 1.1178 | 64.1361 | 69.5844 |
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+ | 1.0895 | 6.9 | 504 | 1.1404 | 63.0890 | 68.6016 |
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+ | 1.0895 | 7.4 | 540 | 1.0862 | 65.7068 | 70.8093 |
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+ | 1.054 | 7.89 | 576 | 1.0959 | 64.7906 | 70.2001 |
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+ | 1.0231 | 8.38 | 612 | 1.1036 | 64.3979 | 69.7053 |
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+ | 1.0231 | 8.87 | 648 | 1.0698 | 65.8377 | 71.1488 |
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+ | 0.9985 | 9.37 | 684 | 1.0777 | 66.0995 | 71.3149 |
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+ | 0.9736 | 9.86 | 720 | 1.0942 | 64.3979 | 69.8535 |
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  ### Framework versions