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sentiment-pt-pl30-2

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  1. README.md +25 -27
  2. runs/Jun03_14-17-29_a358b85c7679/events.out.tfevents.1717424259.a358b85c7679.134923.0 +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: 0.2988
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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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@@ -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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- | 0.541 | 1.0 | 122 | 0.4985 | 0.7293 | 0.6648 | 0.6310 | 0.6397 |
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- | 0.4477 | 2.0 | 244 | 0.4465 | 0.7644 | 0.7427 | 0.7883 | 0.7462 |
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- | 0.347 | 3.0 | 366 | 0.3237 | 0.8647 | 0.8556 | 0.8067 | 0.8255 |
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- | 0.3005 | 4.0 | 488 | 0.2992 | 0.8922 | 0.8734 | 0.8637 | 0.8683 |
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- | 0.281 | 5.0 | 610 | 0.2869 | 0.8647 | 0.8398 | 0.8292 | 0.8342 |
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- | 0.2419 | 6.0 | 732 | 0.2945 | 0.8747 | 0.8443 | 0.8663 | 0.8537 |
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- | 0.2394 | 7.0 | 854 | 0.2835 | 0.8772 | 0.8504 | 0.8556 | 0.8530 |
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- | 0.2192 | 8.0 | 976 | 0.2803 | 0.8772 | 0.8535 | 0.8481 | 0.8507 |
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- | 0.2144 | 9.0 | 1098 | 0.2861 | 0.8747 | 0.8499 | 0.8463 | 0.8481 |
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- | 0.2056 | 10.0 | 1220 | 0.2724 | 0.8922 | 0.8706 | 0.8687 | 0.8697 |
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- | 0.1822 | 11.0 | 1342 | 0.2813 | 0.8872 | 0.8606 | 0.8727 | 0.8662 |
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- | 0.1817 | 12.0 | 1464 | 0.2900 | 0.8872 | 0.8760 | 0.8452 | 0.8584 |
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- | 0.1621 | 13.0 | 1586 | 0.2926 | 0.8947 | 0.8773 | 0.8655 | 0.8711 |
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- | 0.1577 | 14.0 | 1708 | 0.2904 | 0.8922 | 0.8683 | 0.8737 | 0.8710 |
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- | 0.1612 | 15.0 | 1830 | 0.2996 | 0.8847 | 0.8648 | 0.8534 | 0.8588 |
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- | 0.1496 | 16.0 | 1952 | 0.2970 | 0.8872 | 0.8624 | 0.8677 | 0.8650 |
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- | 0.149 | 17.0 | 2074 | 0.2948 | 0.8822 | 0.8574 | 0.8592 | 0.8583 |
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- | 0.1424 | 18.0 | 2196 | 0.2977 | 0.8847 | 0.8609 | 0.8609 | 0.8609 |
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- | 0.1383 | 19.0 | 2318 | 0.2990 | 0.8847 | 0.8621 | 0.8584 | 0.8602 |
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- | 0.1407 | 20.0 | 2440 | 0.2988 | 0.8822 | 0.8574 | 0.8592 | 0.8583 |
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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: 0.2998
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+ - Accuracy: 0.8997
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+ - Precision: 0.8804
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+ - Recall: 0.8766
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+ - F1: 0.8785
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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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+ | 0.5411 | 1.0 | 122 | 0.4939 | 0.7368 | 0.6762 | 0.6413 | 0.6509 |
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+ | 0.4231 | 2.0 | 244 | 0.3852 | 0.8246 | 0.7888 | 0.8184 | 0.7995 |
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+ | 0.3331 | 3.0 | 366 | 0.3313 | 0.8471 | 0.8233 | 0.7968 | 0.8081 |
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+ | 0.2924 | 4.0 | 488 | 0.3057 | 0.8822 | 0.8610 | 0.8517 | 0.8561 |
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+ | 0.2705 | 5.0 | 610 | 0.3069 | 0.8747 | 0.8605 | 0.8288 | 0.8422 |
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+ | 0.2461 | 6.0 | 732 | 0.3119 | 0.8747 | 0.8436 | 0.8763 | 0.8562 |
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+ | 0.2313 | 7.0 | 854 | 0.2880 | 0.8872 | 0.8606 | 0.8727 | 0.8662 |
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+ | 0.2183 | 8.0 | 976 | 0.2773 | 0.8922 | 0.8749 | 0.8612 | 0.8676 |
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+ | 0.2093 | 9.0 | 1098 | 0.2804 | 0.8847 | 0.8648 | 0.8534 | 0.8588 |
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+ | 0.1986 | 10.0 | 1220 | 0.2890 | 0.8922 | 0.8804 | 0.8537 | 0.8655 |
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+ | 0.1881 | 11.0 | 1342 | 0.2911 | 0.8872 | 0.8658 | 0.8602 | 0.8629 |
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+ | 0.1802 | 12.0 | 1464 | 0.2866 | 0.8822 | 0.8596 | 0.8542 | 0.8568 |
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+ | 0.169 | 13.0 | 1586 | 0.2964 | 0.8847 | 0.8697 | 0.8459 | 0.8565 |
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+ | 0.1709 | 14.0 | 1708 | 0.2944 | 0.8872 | 0.8658 | 0.8602 | 0.8629 |
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+ | 0.1492 | 15.0 | 1830 | 0.2866 | 0.8872 | 0.8645 | 0.8627 | 0.8636 |
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+ | 0.1493 | 16.0 | 1952 | 0.2951 | 0.8947 | 0.8708 | 0.8780 | 0.8743 |
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+ | 0.1425 | 17.0 | 2074 | 0.3048 | 0.8947 | 0.8773 | 0.8655 | 0.8711 |
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+ | 0.1375 | 18.0 | 2196 | 0.2987 | 0.8997 | 0.8791 | 0.8791 | 0.8791 |
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+ | 0.1326 | 19.0 | 2318 | 0.3073 | 0.8997 | 0.8819 | 0.8741 | 0.8778 |
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+ | 0.1365 | 20.0 | 2440 | 0.2998 | 0.8997 | 0.8804 | 0.8766 | 0.8785 |
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  ### Framework versions
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