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sentiment-pt-pl10-0

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  1. README.md +25 -27
  2. runs/Jun03_12-49-09_a358b85c7679/events.out.tfevents.1717418959.a358b85c7679.87787.0 +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: 0.2766
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- - Accuracy: 0.9023
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- - Precision: 0.8802
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- - Recall: 0.8858
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- - F1: 0.8830
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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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- | 0.5459 | 1.0 | 122 | 0.4763 | 0.7393 | 0.6804 | 0.6356 | 0.6459 |
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- | 0.4528 | 2.0 | 244 | 0.4306 | 0.7845 | 0.7630 | 0.8125 | 0.7678 |
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- | 0.3653 | 3.0 | 366 | 0.3335 | 0.8622 | 0.8533 | 0.8025 | 0.8217 |
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- | 0.2987 | 4.0 | 488 | 0.3357 | 0.8546 | 0.8246 | 0.8246 | 0.8246 |
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- | 0.2746 | 5.0 | 610 | 0.3401 | 0.8546 | 0.8217 | 0.8547 | 0.8339 |
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- | 0.2477 | 6.0 | 732 | 0.3323 | 0.8496 | 0.8176 | 0.8586 | 0.8308 |
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- | 0.24 | 7.0 | 854 | 0.3171 | 0.8647 | 0.8325 | 0.8642 | 0.8447 |
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- | 0.2069 | 8.0 | 976 | 0.2770 | 0.8922 | 0.8734 | 0.8637 | 0.8683 |
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- | 0.2197 | 9.0 | 1098 | 0.3091 | 0.8672 | 0.8356 | 0.8735 | 0.8491 |
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- | 0.2005 | 10.0 | 1220 | 0.2552 | 0.9023 | 0.8842 | 0.8783 | 0.8812 |
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- | 0.1867 | 11.0 | 1342 | 0.2727 | 0.9048 | 0.8816 | 0.8926 | 0.8868 |
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- | 0.1722 | 12.0 | 1464 | 0.2739 | 0.8922 | 0.8657 | 0.8813 | 0.8728 |
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- | 0.161 | 13.0 | 1586 | 0.2714 | 0.8997 | 0.8852 | 0.8691 | 0.8765 |
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- | 0.1684 | 14.0 | 1708 | 0.2774 | 0.8972 | 0.8723 | 0.8848 | 0.8781 |
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- | 0.1548 | 15.0 | 1830 | 0.2742 | 0.8997 | 0.8767 | 0.8841 | 0.8803 |
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- | 0.1526 | 16.0 | 1952 | 0.2970 | 0.8872 | 0.8574 | 0.8902 | 0.8703 |
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- | 0.1467 | 17.0 | 2074 | 0.2729 | 0.8897 | 0.8618 | 0.8820 | 0.8707 |
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- | 0.1484 | 18.0 | 2196 | 0.2739 | 0.8972 | 0.8723 | 0.8848 | 0.8781 |
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- | 0.1434 | 19.0 | 2318 | 0.2729 | 0.8997 | 0.8778 | 0.8816 | 0.8797 |
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- | 0.1354 | 20.0 | 2440 | 0.2766 | 0.9023 | 0.8802 | 0.8858 | 0.8830 |
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  ### Framework versions
 
1
  ---
 
 
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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: 0.2798
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+ - Accuracy: 0.8972
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+ - Precision: 0.8723
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+ - Recall: 0.8848
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+ - F1: 0.8781
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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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+ | 0.5568 | 1.0 | 122 | 0.4822 | 0.7243 | 0.6557 | 0.6074 | 0.6144 |
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+ | 0.4661 | 2.0 | 244 | 0.4453 | 0.7544 | 0.7241 | 0.7612 | 0.7304 |
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+ | 0.3875 | 3.0 | 366 | 0.3447 | 0.8622 | 0.8488 | 0.8075 | 0.8239 |
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+ | 0.318 | 4.0 | 488 | 0.3442 | 0.8496 | 0.8158 | 0.8436 | 0.8267 |
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+ | 0.2855 | 5.0 | 610 | 0.3349 | 0.8496 | 0.8158 | 0.8411 | 0.8260 |
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+ | 0.2638 | 6.0 | 732 | 0.3548 | 0.8371 | 0.8052 | 0.8472 | 0.8177 |
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+ | 0.2397 | 7.0 | 854 | 0.3254 | 0.8647 | 0.8326 | 0.8592 | 0.8434 |
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+ | 0.2428 | 8.0 | 976 | 0.2799 | 0.8922 | 0.8804 | 0.8537 | 0.8655 |
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+ | 0.2229 | 9.0 | 1098 | 0.2903 | 0.8722 | 0.8431 | 0.8546 | 0.8484 |
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+ | 0.2144 | 10.0 | 1220 | 0.2583 | 0.8972 | 0.8743 | 0.8798 | 0.8770 |
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+ | 0.1967 | 11.0 | 1342 | 0.2743 | 0.8822 | 0.8530 | 0.8742 | 0.8622 |
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+ | 0.1855 | 12.0 | 1464 | 0.2913 | 0.8772 | 0.8473 | 0.8681 | 0.8563 |
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+ | 0.1761 | 13.0 | 1586 | 0.2660 | 0.9023 | 0.8913 | 0.8683 | 0.8786 |
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+ | 0.1733 | 14.0 | 1708 | 0.2868 | 0.8822 | 0.8530 | 0.8742 | 0.8622 |
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+ | 0.1582 | 15.0 | 1830 | 0.2801 | 0.8847 | 0.8561 | 0.8759 | 0.8648 |
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+ | 0.1537 | 16.0 | 1952 | 0.3073 | 0.8747 | 0.8438 | 0.8713 | 0.8550 |
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+ | 0.1537 | 17.0 | 2074 | 0.2702 | 0.8972 | 0.8723 | 0.8848 | 0.8781 |
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+ | 0.1461 | 18.0 | 2196 | 0.2923 | 0.8947 | 0.8682 | 0.8855 | 0.8760 |
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+ | 0.1449 | 19.0 | 2318 | 0.2791 | 0.8947 | 0.8690 | 0.8830 | 0.8755 |
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+ | 0.1502 | 20.0 | 2440 | 0.2798 | 0.8972 | 0.8723 | 0.8848 | 0.8781 |
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  ### Framework versions
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