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sentiment-pt-pl20-3

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  1. README.md +25 -27
  2. runs/Jun03_14-39-35_a358b85c7679/events.out.tfevents.1717425584.a358b85c7679.146701.0 +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: 0.3253
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- - Accuracy: 0.8822
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- - Precision: 0.8564
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- - Recall: 0.8617
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- - F1: 0.8590
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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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- | 0.5445 | 1.0 | 122 | 0.4894 | 0.7519 | 0.6988 | 0.6594 | 0.6708 |
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- | 0.432 | 2.0 | 244 | 0.3691 | 0.8195 | 0.7843 | 0.8173 | 0.7954 |
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- | 0.3342 | 3.0 | 366 | 0.3301 | 0.8496 | 0.8574 | 0.7686 | 0.7957 |
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- | 0.2846 | 4.0 | 488 | 0.2886 | 0.8797 | 0.8633 | 0.8399 | 0.8502 |
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- | 0.2621 | 5.0 | 610 | 0.2728 | 0.8747 | 0.8488 | 0.8488 | 0.8488 |
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- | 0.2419 | 6.0 | 732 | 0.2753 | 0.8747 | 0.8471 | 0.8538 | 0.8503 |
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- | 0.2132 | 7.0 | 854 | 0.2753 | 0.8847 | 0.8589 | 0.8659 | 0.8623 |
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- | 0.2055 | 8.0 | 976 | 0.2791 | 0.8797 | 0.8560 | 0.8524 | 0.8541 |
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- | 0.1903 | 9.0 | 1098 | 0.3009 | 0.8622 | 0.8373 | 0.8250 | 0.8307 |
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- | 0.1852 | 10.0 | 1220 | 0.3085 | 0.8672 | 0.8479 | 0.8235 | 0.8342 |
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- | 0.1758 | 11.0 | 1342 | 0.2852 | 0.8797 | 0.8539 | 0.8574 | 0.8556 |
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- | 0.1617 | 12.0 | 1464 | 0.3011 | 0.8872 | 0.8634 | 0.8652 | 0.8643 |
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- | 0.1581 | 13.0 | 1586 | 0.3050 | 0.8922 | 0.8694 | 0.8712 | 0.8703 |
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- | 0.149 | 14.0 | 1708 | 0.3143 | 0.8922 | 0.8639 | 0.8888 | 0.8745 |
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- | 0.1386 | 15.0 | 1830 | 0.3028 | 0.8997 | 0.8791 | 0.8791 | 0.8791 |
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- | 0.1465 | 16.0 | 1952 | 0.3112 | 0.8922 | 0.8706 | 0.8687 | 0.8697 |
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- | 0.1307 | 17.0 | 2074 | 0.3198 | 0.8847 | 0.8581 | 0.8684 | 0.8629 |
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- | 0.1231 | 18.0 | 2196 | 0.3253 | 0.8847 | 0.8609 | 0.8609 | 0.8609 |
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- | 0.1344 | 19.0 | 2318 | 0.3290 | 0.8797 | 0.8560 | 0.8524 | 0.8541 |
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- | 0.1229 | 20.0 | 2440 | 0.3253 | 0.8822 | 0.8564 | 0.8617 | 0.8590 |
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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:
 
20
 
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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: 0.2974
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+ - Accuracy: 0.8847
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+ - Precision: 0.8609
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+ - Recall: 0.8609
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+ - F1: 0.8609
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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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+ | 0.551 | 1.0 | 122 | 0.5009 | 0.7243 | 0.6557 | 0.6074 | 0.6144 |
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+ | 0.4528 | 2.0 | 244 | 0.4118 | 0.7820 | 0.7487 | 0.7857 | 0.7578 |
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+ | 0.3588 | 3.0 | 366 | 0.3428 | 0.8521 | 0.8440 | 0.7854 | 0.8064 |
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+ | 0.3192 | 4.0 | 488 | 0.3117 | 0.8546 | 0.8246 | 0.8246 | 0.8246 |
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+ | 0.2714 | 5.0 | 610 | 0.3037 | 0.8672 | 0.8359 | 0.8560 | 0.8446 |
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+ | 0.257 | 6.0 | 732 | 0.2833 | 0.8772 | 0.8592 | 0.8381 | 0.8475 |
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+ | 0.2405 | 7.0 | 854 | 0.2861 | 0.8847 | 0.8599 | 0.8634 | 0.8616 |
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+ | 0.2163 | 8.0 | 976 | 0.2954 | 0.8797 | 0.8539 | 0.8574 | 0.8556 |
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+ | 0.2135 | 9.0 | 1098 | 0.2942 | 0.8747 | 0.8510 | 0.8438 | 0.8473 |
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+ | 0.2001 | 10.0 | 1220 | 0.3002 | 0.8822 | 0.8656 | 0.8442 | 0.8537 |
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+ | 0.1825 | 11.0 | 1342 | 0.3011 | 0.8922 | 0.8749 | 0.8612 | 0.8676 |
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+ | 0.1765 | 12.0 | 1464 | 0.2858 | 0.8897 | 0.8695 | 0.8620 | 0.8656 |
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+ | 0.1674 | 13.0 | 1586 | 0.2932 | 0.8947 | 0.8698 | 0.8805 | 0.8749 |
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+ | 0.1597 | 14.0 | 1708 | 0.2937 | 0.8872 | 0.8599 | 0.8752 | 0.8669 |
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+ | 0.1564 | 15.0 | 1830 | 0.2963 | 0.8947 | 0.8757 | 0.8680 | 0.8717 |
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+ | 0.142 | 16.0 | 1952 | 0.3025 | 0.8922 | 0.8734 | 0.8637 | 0.8683 |
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+ | 0.143 | 17.0 | 2074 | 0.2951 | 0.8897 | 0.8649 | 0.8720 | 0.8683 |
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+ | 0.1315 | 18.0 | 2196 | 0.3013 | 0.8822 | 0.8574 | 0.8592 | 0.8583 |
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+ | 0.1378 | 19.0 | 2318 | 0.3038 | 0.8872 | 0.8658 | 0.8602 | 0.8629 |
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+ | 0.1333 | 20.0 | 2440 | 0.2974 | 0.8847 | 0.8609 | 0.8609 | 0.8609 |
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  ### Framework versions
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