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sentiment-pt-pl10-3

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  1. README.md +25 -27
  2. runs/Jun03_14-28-41_a358b85c7679/events.out.tfevents.1717424930.a358b85c7679.140888.0 +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: 0.2824
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- - Accuracy: 0.8897
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- - Precision: 0.8710
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- - Recall: 0.8595
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- - F1: 0.8649
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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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- | 0.5526 | 1.0 | 122 | 0.5089 | 0.7143 | 0.6432 | 0.6178 | 0.6246 |
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- | 0.4578 | 2.0 | 244 | 0.4194 | 0.7995 | 0.7620 | 0.7906 | 0.7718 |
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- | 0.3632 | 3.0 | 366 | 0.3468 | 0.8371 | 0.8222 | 0.7672 | 0.7867 |
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- | 0.3063 | 4.0 | 488 | 0.2975 | 0.8822 | 0.8564 | 0.8617 | 0.8590 |
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- | 0.2771 | 5.0 | 610 | 0.3195 | 0.8722 | 0.8409 | 0.8696 | 0.8524 |
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- | 0.2463 | 6.0 | 732 | 0.2897 | 0.8772 | 0.8496 | 0.8581 | 0.8537 |
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- | 0.2317 | 7.0 | 854 | 0.2718 | 0.8847 | 0.8609 | 0.8609 | 0.8609 |
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- | 0.2182 | 8.0 | 976 | 0.2683 | 0.8847 | 0.8556 | 0.8784 | 0.8654 |
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- | 0.2065 | 9.0 | 1098 | 0.2773 | 0.8697 | 0.8411 | 0.8478 | 0.8443 |
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- | 0.2012 | 10.0 | 1220 | 0.2841 | 0.8822 | 0.8674 | 0.8417 | 0.8529 |
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- | 0.1944 | 11.0 | 1342 | 0.2733 | 0.8847 | 0.8599 | 0.8634 | 0.8616 |
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- | 0.176 | 12.0 | 1464 | 0.2709 | 0.8972 | 0.8849 | 0.8623 | 0.8724 |
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- | 0.168 | 13.0 | 1586 | 0.2651 | 0.8947 | 0.8718 | 0.8755 | 0.8737 |
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- | 0.1644 | 14.0 | 1708 | 0.2711 | 0.8922 | 0.8657 | 0.8813 | 0.8728 |
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- | 0.1541 | 15.0 | 1830 | 0.2790 | 0.8922 | 0.8734 | 0.8637 | 0.8683 |
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- | 0.1574 | 16.0 | 1952 | 0.2767 | 0.8897 | 0.8695 | 0.8620 | 0.8656 |
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- | 0.1508 | 17.0 | 2074 | 0.2826 | 0.8897 | 0.8659 | 0.8695 | 0.8676 |
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- | 0.1463 | 18.0 | 2196 | 0.2824 | 0.8872 | 0.8687 | 0.8552 | 0.8615 |
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- | 0.1467 | 19.0 | 2318 | 0.2876 | 0.8847 | 0.8679 | 0.8484 | 0.8573 |
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- | 0.1399 | 20.0 | 2440 | 0.2824 | 0.8897 | 0.8710 | 0.8595 | 0.8649 |
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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: 0.3389
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+ - Accuracy: 0.8822
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+ - Precision: 0.8574
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+ - Recall: 0.8592
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+ - F1: 0.8583
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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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+ | 0.5509 | 1.0 | 122 | 0.4983 | 0.7393 | 0.6801 | 0.6406 | 0.6507 |
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+ | 0.4511 | 2.0 | 244 | 0.4377 | 0.7769 | 0.7547 | 0.8022 | 0.7593 |
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+ | 0.368 | 3.0 | 366 | 0.3260 | 0.8571 | 0.8381 | 0.8064 | 0.8196 |
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+ | 0.3019 | 4.0 | 488 | 0.3036 | 0.8647 | 0.8410 | 0.8267 | 0.8333 |
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+ | 0.2668 | 5.0 | 610 | 0.3192 | 0.8672 | 0.8372 | 0.8485 | 0.8425 |
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+ | 0.2471 | 6.0 | 732 | 0.3059 | 0.8622 | 0.8305 | 0.8475 | 0.8380 |
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+ | 0.2422 | 7.0 | 854 | 0.2950 | 0.8747 | 0.8451 | 0.8613 | 0.8524 |
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+ | 0.2258 | 8.0 | 976 | 0.2928 | 0.8722 | 0.8463 | 0.8446 | 0.8454 |
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+ | 0.2054 | 9.0 | 1098 | 0.3049 | 0.8797 | 0.8572 | 0.8499 | 0.8534 |
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+ | 0.2009 | 10.0 | 1220 | 0.3013 | 0.8747 | 0.8488 | 0.8488 | 0.8488 |
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+ | 0.1755 | 11.0 | 1342 | 0.3070 | 0.8822 | 0.8574 | 0.8592 | 0.8583 |
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+ | 0.1821 | 12.0 | 1464 | 0.2995 | 0.8822 | 0.8596 | 0.8542 | 0.8568 |
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+ | 0.1652 | 13.0 | 1586 | 0.3272 | 0.8847 | 0.8553 | 0.8809 | 0.8660 |
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+ | 0.1566 | 14.0 | 1708 | 0.3336 | 0.8897 | 0.8609 | 0.8870 | 0.8719 |
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+ | 0.1634 | 15.0 | 1830 | 0.3150 | 0.8847 | 0.8589 | 0.8659 | 0.8623 |
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+ | 0.1496 | 16.0 | 1952 | 0.3321 | 0.8922 | 0.8706 | 0.8687 | 0.8697 |
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+ | 0.1355 | 17.0 | 2074 | 0.3276 | 0.8847 | 0.8599 | 0.8634 | 0.8616 |
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+ | 0.1477 | 18.0 | 2196 | 0.3365 | 0.8797 | 0.8530 | 0.8599 | 0.8563 |
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+ | 0.1317 | 19.0 | 2318 | 0.3385 | 0.8822 | 0.8574 | 0.8592 | 0.8583 |
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+ | 0.1267 | 20.0 | 2440 | 0.3389 | 0.8822 | 0.8574 | 0.8592 | 0.8583 |
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  ### Framework versions
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