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sentiment-pt-pl30-0

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  1. README.md +25 -27
  2. runs/Jun03_13-11-00_a358b85c7679/events.out.tfevents.1717420270.a358b85c7679.99454.0 +2 -2
  3. sentiment-pt/pytorch_adapter.bin +1 -1
  4. sentiment/pytorch_model_head.bin +1 -1
README.md CHANGED
@@ -1,6 +1,4 @@
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  ---
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- language:
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- - id
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  license: mit
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  base_model: indolem/indobert-base-uncased
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  tags:
@@ -22,11 +20,11 @@ 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 an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.2913
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- - Accuracy: 0.9048
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- - Precision: 0.8851
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- - Recall: 0.8851
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- - F1: 0.8851
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  ## Model description
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@@ -57,26 +55,26 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
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- | 0.5457 | 1.0 | 122 | 0.4753 | 0.7193 | 0.6465 | 0.5964 | 0.6014 |
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- | 0.4518 | 2.0 | 244 | 0.4070 | 0.7970 | 0.7589 | 0.7864 | 0.7685 |
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- | 0.3461 | 3.0 | 366 | 0.3412 | 0.8421 | 0.8231 | 0.7808 | 0.7970 |
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- | 0.2958 | 4.0 | 488 | 0.3253 | 0.8546 | 0.8263 | 0.8196 | 0.8229 |
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- | 0.2659 | 5.0 | 610 | 0.2941 | 0.8822 | 0.8610 | 0.8517 | 0.8561 |
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- | 0.2482 | 6.0 | 732 | 0.2965 | 0.8772 | 0.8473 | 0.8681 | 0.8563 |
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- | 0.2264 | 7.0 | 854 | 0.2869 | 0.8747 | 0.8447 | 0.8638 | 0.8531 |
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- | 0.2218 | 8.0 | 976 | 0.2795 | 0.8997 | 0.8961 | 0.8566 | 0.8730 |
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- | 0.2106 | 9.0 | 1098 | 0.2705 | 0.8922 | 0.8673 | 0.8763 | 0.8716 |
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- | 0.1981 | 10.0 | 1220 | 0.2751 | 0.9073 | 0.8920 | 0.8819 | 0.8867 |
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- | 0.1802 | 11.0 | 1342 | 0.2745 | 0.9048 | 0.8826 | 0.8901 | 0.8862 |
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- | 0.1828 | 12.0 | 1464 | 0.2799 | 0.9073 | 0.8957 | 0.8769 | 0.8855 |
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- | 0.1707 | 13.0 | 1586 | 0.2739 | 0.9098 | 0.8960 | 0.8837 | 0.8895 |
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- | 0.1606 | 14.0 | 1708 | 0.2868 | 0.9073 | 0.8862 | 0.8919 | 0.8890 |
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- | 0.1499 | 15.0 | 1830 | 0.2930 | 0.9023 | 0.8828 | 0.8808 | 0.8818 |
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- | 0.1555 | 16.0 | 1952 | 0.3041 | 0.8947 | 0.8682 | 0.8855 | 0.8760 |
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- | 0.1396 | 17.0 | 2074 | 0.2876 | 0.9023 | 0.8814 | 0.8833 | 0.8824 |
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- | 0.1477 | 18.0 | 2196 | 0.2900 | 0.9048 | 0.8865 | 0.8826 | 0.8845 |
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- | 0.1434 | 19.0 | 2318 | 0.2917 | 0.9048 | 0.8851 | 0.8851 | 0.8851 |
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- | 0.1386 | 20.0 | 2440 | 0.2913 | 0.9048 | 0.8851 | 0.8851 | 0.8851 |
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  ### Framework versions
 
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  ---
 
 
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  license: mit
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  base_model: indolem/indobert-base-uncased
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  tags:
 
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  This model is a fine-tuned version of [indolem/indobert-base-uncased](https://huggingface.co/indolem/indobert-base-uncased) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.2793
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+ - Accuracy: 0.8922
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+ - Precision: 0.8665
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+ - Recall: 0.8788
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+ - F1: 0.8722
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
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+ | 0.5424 | 1.0 | 122 | 0.4762 | 0.7419 | 0.6837 | 0.6473 | 0.6575 |
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+ | 0.4345 | 2.0 | 244 | 0.4157 | 0.7895 | 0.7581 | 0.7986 | 0.7674 |
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+ | 0.3391 | 3.0 | 366 | 0.3388 | 0.8546 | 0.8324 | 0.8071 | 0.8180 |
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+ | 0.2837 | 4.0 | 488 | 0.3279 | 0.8622 | 0.8342 | 0.8325 | 0.8333 |
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+ | 0.2761 | 5.0 | 610 | 0.3132 | 0.8647 | 0.8346 | 0.8442 | 0.8391 |
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+ | 0.2459 | 6.0 | 732 | 0.3033 | 0.8747 | 0.8440 | 0.8688 | 0.8544 |
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+ | 0.2321 | 7.0 | 854 | 0.2871 | 0.8822 | 0.8530 | 0.8742 | 0.8622 |
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+ | 0.2206 | 8.0 | 976 | 0.2634 | 0.8822 | 0.8610 | 0.8517 | 0.8561 |
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+ | 0.2067 | 9.0 | 1098 | 0.2634 | 0.8922 | 0.8694 | 0.8712 | 0.8703 |
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+ | 0.192 | 10.0 | 1220 | 0.2696 | 0.8922 | 0.8873 | 0.8462 | 0.8631 |
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+ | 0.1866 | 11.0 | 1342 | 0.2752 | 0.8972 | 0.8691 | 0.8973 | 0.8808 |
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+ | 0.1786 | 12.0 | 1464 | 0.2652 | 0.8972 | 0.8708 | 0.8898 | 0.8793 |
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+ | 0.1695 | 13.0 | 1586 | 0.2536 | 0.9073 | 0.8920 | 0.8819 | 0.8867 |
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+ | 0.1664 | 14.0 | 1708 | 0.2737 | 0.8872 | 0.8587 | 0.8802 | 0.8681 |
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+ | 0.1521 | 15.0 | 1830 | 0.2620 | 0.9023 | 0.8802 | 0.8858 | 0.8830 |
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+ | 0.1494 | 16.0 | 1952 | 0.3030 | 0.8922 | 0.8630 | 0.8963 | 0.8761 |
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+ | 0.1487 | 17.0 | 2074 | 0.2702 | 0.8922 | 0.8650 | 0.8838 | 0.8734 |
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+ | 0.1494 | 18.0 | 2196 | 0.2763 | 0.8947 | 0.8676 | 0.8880 | 0.8766 |
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+ | 0.1334 | 19.0 | 2318 | 0.2826 | 0.8922 | 0.8650 | 0.8838 | 0.8734 |
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+ | 0.1325 | 20.0 | 2440 | 0.2793 | 0.8922 | 0.8665 | 0.8788 | 0.8722 |
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  ### Framework versions
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