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sentiment-pt-pl30-4

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  1. README.md +25 -27
  2. runs/Jun03_15-23-46_a358b85c7679/events.out.tfevents.1717428236.a358b85c7679.170314.0 +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: 0.3072
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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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- | 0.5438 | 1.0 | 122 | 0.4988 | 0.7218 | 0.6601 | 0.6507 | 0.6546 |
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- | 0.4428 | 2.0 | 244 | 0.3788 | 0.8446 | 0.8107 | 0.8226 | 0.8161 |
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- | 0.3441 | 3.0 | 366 | 0.3289 | 0.8596 | 0.8510 | 0.7982 | 0.8179 |
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- | 0.2986 | 4.0 | 488 | 0.2884 | 0.8797 | 0.8572 | 0.8499 | 0.8534 |
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- | 0.2667 | 5.0 | 610 | 0.2698 | 0.8772 | 0.8535 | 0.8481 | 0.8507 |
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- | 0.2524 | 6.0 | 732 | 0.2723 | 0.8847 | 0.8609 | 0.8609 | 0.8609 |
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- | 0.2343 | 7.0 | 854 | 0.3180 | 0.8647 | 0.8533 | 0.8092 | 0.8266 |
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- | 0.2212 | 8.0 | 976 | 0.2949 | 0.8822 | 0.8674 | 0.8417 | 0.8529 |
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- | 0.2142 | 9.0 | 1098 | 0.2828 | 0.8847 | 0.8697 | 0.8459 | 0.8565 |
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- | 0.1958 | 10.0 | 1220 | 0.2887 | 0.8697 | 0.8399 | 0.8528 | 0.8458 |
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- | 0.1855 | 11.0 | 1342 | 0.2868 | 0.8822 | 0.8548 | 0.8667 | 0.8603 |
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- | 0.1742 | 12.0 | 1464 | 0.2981 | 0.8747 | 0.8552 | 0.8363 | 0.8448 |
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- | 0.1601 | 13.0 | 1586 | 0.2930 | 0.8797 | 0.8539 | 0.8574 | 0.8556 |
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- | 0.1602 | 14.0 | 1708 | 0.2979 | 0.8797 | 0.8504 | 0.8699 | 0.8590 |
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- | 0.1497 | 15.0 | 1830 | 0.2969 | 0.8872 | 0.8606 | 0.8727 | 0.8662 |
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- | 0.1447 | 16.0 | 1952 | 0.2963 | 0.8847 | 0.8599 | 0.8634 | 0.8616 |
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- | 0.1394 | 17.0 | 2074 | 0.3018 | 0.8822 | 0.8564 | 0.8617 | 0.8590 |
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- | 0.1333 | 18.0 | 2196 | 0.3065 | 0.8822 | 0.8574 | 0.8592 | 0.8583 |
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- | 0.1406 | 19.0 | 2318 | 0.3062 | 0.8822 | 0.8574 | 0.8592 | 0.8583 |
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- | 0.1243 | 20.0 | 2440 | 0.3072 | 0.8822 | 0.8574 | 0.8592 | 0.8583 |
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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: 0.3168
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+ - Accuracy: 0.8797
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+ - Precision: 0.8530
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+ - Recall: 0.8599
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+ - F1: 0.8563
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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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+ | 0.5413 | 1.0 | 122 | 0.5007 | 0.7243 | 0.6593 | 0.6374 | 0.6446 |
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+ | 0.4584 | 2.0 | 244 | 0.3856 | 0.8296 | 0.8123 | 0.7569 | 0.7761 |
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+ | 0.3559 | 3.0 | 366 | 0.3407 | 0.8571 | 0.8638 | 0.7814 | 0.8079 |
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+ | 0.2961 | 4.0 | 488 | 0.3089 | 0.8697 | 0.8438 | 0.8403 | 0.8420 |
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+ | 0.276 | 5.0 | 610 | 0.2917 | 0.8622 | 0.8314 | 0.8425 | 0.8365 |
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+ | 0.2555 | 6.0 | 732 | 0.2905 | 0.8697 | 0.8428 | 0.8428 | 0.8428 |
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+ | 0.2427 | 7.0 | 854 | 0.3031 | 0.8772 | 0.8670 | 0.8281 | 0.8440 |
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+ | 0.2219 | 8.0 | 976 | 0.2908 | 0.8772 | 0.8514 | 0.8531 | 0.8522 |
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+ | 0.2158 | 9.0 | 1098 | 0.3084 | 0.8847 | 0.8760 | 0.8384 | 0.8540 |
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+ | 0.2 | 10.0 | 1220 | 0.2938 | 0.8747 | 0.8457 | 0.8588 | 0.8517 |
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+ | 0.1885 | 11.0 | 1342 | 0.2977 | 0.8772 | 0.8524 | 0.8506 | 0.8515 |
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+ | 0.183 | 12.0 | 1464 | 0.3070 | 0.8847 | 0.8717 | 0.8434 | 0.8557 |
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+ | 0.1752 | 13.0 | 1586 | 0.2959 | 0.8797 | 0.8522 | 0.8624 | 0.8570 |
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+ | 0.1558 | 14.0 | 1708 | 0.3040 | 0.8747 | 0.8447 | 0.8638 | 0.8531 |
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+ | 0.1538 | 15.0 | 1830 | 0.3082 | 0.8722 | 0.8431 | 0.8546 | 0.8484 |
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+ | 0.152 | 16.0 | 1952 | 0.3100 | 0.8772 | 0.8576 | 0.8406 | 0.8484 |
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+ | 0.1436 | 17.0 | 2074 | 0.3105 | 0.8747 | 0.8463 | 0.8563 | 0.8510 |
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+ | 0.1426 | 18.0 | 2196 | 0.3119 | 0.8747 | 0.8471 | 0.8538 | 0.8503 |
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+ | 0.1398 | 19.0 | 2318 | 0.3164 | 0.8797 | 0.8522 | 0.8624 | 0.8570 |
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+ | 0.14 | 20.0 | 2440 | 0.3168 | 0.8797 | 0.8530 | 0.8599 | 0.8563 |
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  ### Framework versions
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