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sentiment-pt-pl10-4

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  1. README.md +25 -27
  2. runs/Jun03_15-01-46_a358b85c7679/events.out.tfevents.1717426916.a358b85c7679.158543.0 +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: 0.2951
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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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@@ -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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- | 0.5448 | 1.0 | 122 | 0.5047 | 0.7243 | 0.6629 | 0.6524 | 0.6568 |
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- | 0.4527 | 2.0 | 244 | 0.4320 | 0.7945 | 0.7667 | 0.8121 | 0.7752 |
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- | 0.3603 | 3.0 | 366 | 0.3370 | 0.8471 | 0.8393 | 0.7768 | 0.7985 |
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- | 0.3081 | 4.0 | 488 | 0.2995 | 0.8722 | 0.8453 | 0.8471 | 0.8462 |
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- | 0.2793 | 5.0 | 610 | 0.3008 | 0.8747 | 0.8537 | 0.8388 | 0.8457 |
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- | 0.2526 | 6.0 | 732 | 0.2987 | 0.8697 | 0.8449 | 0.8378 | 0.8412 |
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- | 0.2478 | 7.0 | 854 | 0.3030 | 0.8772 | 0.8609 | 0.8356 | 0.8467 |
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- | 0.2337 | 8.0 | 976 | 0.2974 | 0.8672 | 0.8463 | 0.8260 | 0.8351 |
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- | 0.217 | 9.0 | 1098 | 0.2774 | 0.8722 | 0.8562 | 0.8271 | 0.8395 |
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- | 0.1966 | 10.0 | 1220 | 0.2846 | 0.8697 | 0.8411 | 0.8478 | 0.8443 |
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- | 0.199 | 11.0 | 1342 | 0.2910 | 0.8822 | 0.8639 | 0.8467 | 0.8545 |
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- | 0.187 | 12.0 | 1464 | 0.2871 | 0.8772 | 0.8609 | 0.8356 | 0.8467 |
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- | 0.1812 | 13.0 | 1586 | 0.2813 | 0.8797 | 0.8585 | 0.8474 | 0.8526 |
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- | 0.1633 | 14.0 | 1708 | 0.2957 | 0.8822 | 0.8555 | 0.8642 | 0.8596 |
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- | 0.1607 | 15.0 | 1830 | 0.2875 | 0.8922 | 0.8706 | 0.8687 | 0.8697 |
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- | 0.1584 | 16.0 | 1952 | 0.2859 | 0.8822 | 0.8610 | 0.8517 | 0.8561 |
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- | 0.1535 | 17.0 | 2074 | 0.2924 | 0.8847 | 0.8609 | 0.8609 | 0.8609 |
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- | 0.1432 | 18.0 | 2196 | 0.2966 | 0.8847 | 0.8599 | 0.8634 | 0.8616 |
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- | 0.1466 | 19.0 | 2318 | 0.2947 | 0.8822 | 0.8596 | 0.8542 | 0.8568 |
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- | 0.1411 | 20.0 | 2440 | 0.2951 | 0.8847 | 0.8609 | 0.8609 | 0.8609 |
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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: 0.3026
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+ - Accuracy: 0.8822
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+ - Precision: 0.8624
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+ - Recall: 0.8492
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+ - F1: 0.8553
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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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+ | 0.5514 | 1.0 | 122 | 0.5084 | 0.7218 | 0.6601 | 0.6507 | 0.6546 |
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+ | 0.4753 | 2.0 | 244 | 0.4007 | 0.8170 | 0.7870 | 0.7530 | 0.7662 |
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+ | 0.3834 | 3.0 | 366 | 0.3542 | 0.8396 | 0.8449 | 0.7540 | 0.7805 |
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+ | 0.3188 | 4.0 | 488 | 0.3214 | 0.8622 | 0.8342 | 0.8325 | 0.8333 |
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+ | 0.2981 | 5.0 | 610 | 0.2984 | 0.8822 | 0.8624 | 0.8492 | 0.8553 |
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+ | 0.2835 | 6.0 | 732 | 0.2810 | 0.8697 | 0.8520 | 0.8253 | 0.8368 |
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+ | 0.2517 | 7.0 | 854 | 0.2866 | 0.8872 | 0.8672 | 0.8577 | 0.8622 |
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+ | 0.2374 | 8.0 | 976 | 0.2997 | 0.8797 | 0.8671 | 0.8349 | 0.8485 |
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+ | 0.2293 | 9.0 | 1098 | 0.2909 | 0.8797 | 0.8600 | 0.8449 | 0.8518 |
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+ | 0.2091 | 10.0 | 1220 | 0.2928 | 0.8822 | 0.8564 | 0.8617 | 0.8590 |
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+ | 0.198 | 11.0 | 1342 | 0.2847 | 0.8797 | 0.8522 | 0.8624 | 0.8570 |
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+ | 0.1906 | 12.0 | 1464 | 0.3120 | 0.8747 | 0.8586 | 0.8313 | 0.8431 |
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+ | 0.1818 | 13.0 | 1586 | 0.2906 | 0.8772 | 0.8535 | 0.8481 | 0.8507 |
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+ | 0.1756 | 14.0 | 1708 | 0.2810 | 0.8772 | 0.8524 | 0.8506 | 0.8515 |
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+ | 0.174 | 15.0 | 1830 | 0.2829 | 0.8847 | 0.8634 | 0.8559 | 0.8595 |
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+ | 0.1705 | 16.0 | 1952 | 0.2922 | 0.8822 | 0.8624 | 0.8492 | 0.8553 |
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+ | 0.1509 | 17.0 | 2074 | 0.2991 | 0.8822 | 0.8596 | 0.8542 | 0.8568 |
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+ | 0.1549 | 18.0 | 2196 | 0.3000 | 0.8822 | 0.8624 | 0.8492 | 0.8553 |
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+ | 0.1469 | 19.0 | 2318 | 0.2943 | 0.8847 | 0.8609 | 0.8609 | 0.8609 |
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+ | 0.1493 | 20.0 | 2440 | 0.3026 | 0.8822 | 0.8624 | 0.8492 | 0.8553 |
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  ### Framework versions
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