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sentiment-pt-pl20-1

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  1. README.md +25 -27
  2. runs/Jun03_13-33-12_a358b85c7679/events.out.tfevents.1717421601.a358b85c7679.111292.0 +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: 0.2937
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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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- | 0.5467 | 1.0 | 122 | 0.4994 | 0.7444 | 0.6878 | 0.6466 | 0.6574 |
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- | 0.4498 | 2.0 | 244 | 0.4013 | 0.7970 | 0.7568 | 0.7764 | 0.7646 |
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- | 0.3643 | 3.0 | 366 | 0.3603 | 0.8296 | 0.8252 | 0.7444 | 0.7685 |
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- | 0.3131 | 4.0 | 488 | 0.3134 | 0.8546 | 0.8357 | 0.8021 | 0.8159 |
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- | 0.2812 | 5.0 | 610 | 0.3087 | 0.8672 | 0.8463 | 0.8260 | 0.8351 |
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- | 0.2579 | 6.0 | 732 | 0.3037 | 0.8747 | 0.8443 | 0.8663 | 0.8537 |
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- | 0.242 | 7.0 | 854 | 0.2869 | 0.8772 | 0.8514 | 0.8531 | 0.8522 |
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- | 0.2238 | 8.0 | 976 | 0.3086 | 0.8622 | 0.8488 | 0.8075 | 0.8239 |
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- | 0.2134 | 9.0 | 1098 | 0.2916 | 0.8697 | 0.8520 | 0.8253 | 0.8368 |
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- | 0.2014 | 10.0 | 1220 | 0.3077 | 0.8697 | 0.8579 | 0.8178 | 0.8340 |
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- | 0.1918 | 11.0 | 1342 | 0.2910 | 0.8672 | 0.8385 | 0.8435 | 0.8409 |
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- | 0.1764 | 12.0 | 1464 | 0.2865 | 0.8797 | 0.8530 | 0.8599 | 0.8563 |
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- | 0.1771 | 13.0 | 1586 | 0.3068 | 0.8697 | 0.8520 | 0.8253 | 0.8368 |
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- | 0.1708 | 14.0 | 1708 | 0.2962 | 0.8872 | 0.8587 | 0.8802 | 0.8681 |
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- | 0.1585 | 15.0 | 1830 | 0.2889 | 0.8872 | 0.8645 | 0.8627 | 0.8636 |
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- | 0.1602 | 16.0 | 1952 | 0.2941 | 0.8822 | 0.8541 | 0.8692 | 0.8609 |
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- | 0.1481 | 17.0 | 2074 | 0.2971 | 0.8847 | 0.8634 | 0.8559 | 0.8595 |
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- | 0.1536 | 18.0 | 2196 | 0.2937 | 0.8847 | 0.8621 | 0.8584 | 0.8602 |
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- | 0.147 | 19.0 | 2318 | 0.2946 | 0.8822 | 0.8596 | 0.8542 | 0.8568 |
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- | 0.1379 | 20.0 | 2440 | 0.2937 | 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: 0.3296
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+ - Accuracy: 0.8872
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+ - Precision: 0.8624
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+ - Recall: 0.8677
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+ - F1: 0.8650
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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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+ | 0.5524 | 1.0 | 122 | 0.5143 | 0.7168 | 0.6417 | 0.5921 | 0.5963 |
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+ | 0.468 | 2.0 | 244 | 0.4272 | 0.7920 | 0.7507 | 0.7678 | 0.7577 |
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+ | 0.3759 | 3.0 | 366 | 0.3480 | 0.8346 | 0.8175 | 0.7655 | 0.7841 |
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+ | 0.3116 | 4.0 | 488 | 0.3080 | 0.8647 | 0.8439 | 0.8217 | 0.8315 |
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+ | 0.2812 | 5.0 | 610 | 0.3000 | 0.8697 | 0.8520 | 0.8253 | 0.8368 |
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+ | 0.2692 | 6.0 | 732 | 0.2970 | 0.8772 | 0.8473 | 0.8681 | 0.8563 |
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+ | 0.2603 | 7.0 | 854 | 0.2929 | 0.8772 | 0.8489 | 0.8606 | 0.8544 |
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+ | 0.231 | 8.0 | 976 | 0.3083 | 0.8596 | 0.8486 | 0.8007 | 0.8190 |
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+ | 0.2278 | 9.0 | 1098 | 0.2939 | 0.8697 | 0.8428 | 0.8428 | 0.8428 |
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+ | 0.2117 | 10.0 | 1220 | 0.3240 | 0.8747 | 0.8647 | 0.8238 | 0.8404 |
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+ | 0.2014 | 11.0 | 1342 | 0.2902 | 0.8797 | 0.8572 | 0.8499 | 0.8534 |
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+ | 0.1869 | 12.0 | 1464 | 0.2760 | 0.8947 | 0.8698 | 0.8805 | 0.8749 |
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+ | 0.1685 | 13.0 | 1586 | 0.3016 | 0.8822 | 0.8610 | 0.8517 | 0.8561 |
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+ | 0.1703 | 14.0 | 1708 | 0.3027 | 0.8897 | 0.8632 | 0.8770 | 0.8695 |
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+ | 0.1617 | 15.0 | 1830 | 0.3020 | 0.8897 | 0.8632 | 0.8770 | 0.8695 |
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+ | 0.1524 | 16.0 | 1952 | 0.3177 | 0.8822 | 0.8530 | 0.8742 | 0.8622 |
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+ | 0.1356 | 17.0 | 2074 | 0.3291 | 0.8897 | 0.8649 | 0.8720 | 0.8683 |
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+ | 0.1474 | 18.0 | 2196 | 0.3268 | 0.8897 | 0.8649 | 0.8720 | 0.8683 |
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+ | 0.145 | 19.0 | 2318 | 0.3315 | 0.8872 | 0.8614 | 0.8702 | 0.8656 |
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+ | 0.1466 | 20.0 | 2440 | 0.3296 | 0.8872 | 0.8624 | 0.8677 | 0.8650 |
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  ### Framework versions
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