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sentiment-unipelt-0

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  1. README.md +25 -27
  2. runs/Jun03_15-35-02_a358b85c7679/events.out.tfevents.1717428912.a358b85c7679.176319.0 +2 -2
  3. sentiment-unipelt/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: 0.2811
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- - Accuracy: 0.9023
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- - Precision: 0.8773
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- - Recall: 0.8933
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- - F1: 0.8846
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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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- | 0.5459 | 1.0 | 122 | 0.4639 | 0.7469 | 0.6922 | 0.6459 | 0.6573 |
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- | 0.4335 | 2.0 | 244 | 0.4108 | 0.7845 | 0.7552 | 0.7975 | 0.7634 |
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- | 0.3375 | 3.0 | 366 | 0.3283 | 0.8596 | 0.8347 | 0.8207 | 0.8272 |
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- | 0.2801 | 4.0 | 488 | 0.3202 | 0.8596 | 0.8278 | 0.8432 | 0.8347 |
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- | 0.2572 | 5.0 | 610 | 0.3109 | 0.8747 | 0.8438 | 0.8713 | 0.8550 |
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- | 0.2339 | 6.0 | 732 | 0.3074 | 0.8672 | 0.8353 | 0.8660 | 0.8473 |
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- | 0.2249 | 7.0 | 854 | 0.2915 | 0.8672 | 0.8353 | 0.8660 | 0.8473 |
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- | 0.193 | 8.0 | 976 | 0.2540 | 0.8972 | 0.8781 | 0.8723 | 0.8751 |
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- | 0.1899 | 9.0 | 1098 | 0.2636 | 0.8822 | 0.8526 | 0.8767 | 0.8628 |
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- | 0.1801 | 10.0 | 1220 | 0.2371 | 0.9073 | 0.8840 | 0.8969 | 0.8900 |
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- | 0.157 | 11.0 | 1342 | 0.2567 | 0.8997 | 0.8733 | 0.8941 | 0.8825 |
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- | 0.1553 | 12.0 | 1464 | 0.2593 | 0.8972 | 0.8708 | 0.8898 | 0.8793 |
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- | 0.1381 | 13.0 | 1586 | 0.2490 | 0.9173 | 0.9010 | 0.8990 | 0.9000 |
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- | 0.1476 | 14.0 | 1708 | 0.2701 | 0.8997 | 0.8740 | 0.8916 | 0.8819 |
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- | 0.1447 | 15.0 | 1830 | 0.2611 | 0.9123 | 0.8899 | 0.9029 | 0.8960 |
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- | 0.1336 | 16.0 | 1952 | 0.3100 | 0.8997 | 0.8718 | 0.9016 | 0.8840 |
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- | 0.1192 | 17.0 | 2074 | 0.2935 | 0.8972 | 0.8696 | 0.8948 | 0.8803 |
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- | 0.1247 | 18.0 | 2196 | 0.2869 | 0.9023 | 0.8765 | 0.8958 | 0.8851 |
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- | 0.117 | 19.0 | 2318 | 0.2761 | 0.9023 | 0.8773 | 0.8933 | 0.8846 |
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- | 0.1092 | 20.0 | 2440 | 0.2811 | 0.9023 | 0.8773 | 0.8933 | 0.8846 |
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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: 0.3013
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+ - Accuracy: 0.8922
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+ - Precision: 0.8694
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+ - Recall: 0.8712
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+ - F1: 0.8703
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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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+ | 0.5538 | 1.0 | 122 | 0.4789 | 0.7193 | 0.6517 | 0.6289 | 0.6359 |
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+ | 0.4356 | 2.0 | 244 | 0.4088 | 0.7845 | 0.7518 | 0.7900 | 0.7610 |
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+ | 0.3417 | 3.0 | 366 | 0.3369 | 0.8571 | 0.8365 | 0.8089 | 0.8206 |
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+ | 0.2904 | 4.0 | 488 | 0.3267 | 0.8672 | 0.8423 | 0.8335 | 0.8377 |
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+ | 0.263 | 5.0 | 610 | 0.3210 | 0.8672 | 0.8356 | 0.8585 | 0.8453 |
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+ | 0.2463 | 6.0 | 732 | 0.3551 | 0.8421 | 0.8093 | 0.8483 | 0.8220 |
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+ | 0.2303 | 7.0 | 854 | 0.3028 | 0.8722 | 0.8409 | 0.8696 | 0.8524 |
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+ | 0.2208 | 8.0 | 976 | 0.2673 | 0.8897 | 0.8695 | 0.8620 | 0.8656 |
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+ | 0.1994 | 9.0 | 1098 | 0.2715 | 0.8897 | 0.8649 | 0.8720 | 0.8683 |
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+ | 0.1836 | 10.0 | 1220 | 0.2595 | 0.9098 | 0.8999 | 0.8787 | 0.8883 |
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+ | 0.1706 | 11.0 | 1342 | 0.2833 | 0.8922 | 0.8650 | 0.8838 | 0.8734 |
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+ | 0.1623 | 12.0 | 1464 | 0.2993 | 0.8872 | 0.8599 | 0.8752 | 0.8669 |
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+ | 0.1478 | 13.0 | 1586 | 0.2864 | 0.8972 | 0.8849 | 0.8623 | 0.8724 |
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+ | 0.1467 | 14.0 | 1708 | 0.2805 | 0.8972 | 0.8754 | 0.8773 | 0.8764 |
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+ | 0.132 | 15.0 | 1830 | 0.2869 | 0.8997 | 0.8748 | 0.8891 | 0.8814 |
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+ | 0.125 | 16.0 | 1952 | 0.3052 | 0.8972 | 0.8723 | 0.8848 | 0.8781 |
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+ | 0.1183 | 17.0 | 2074 | 0.2968 | 0.8897 | 0.8649 | 0.8720 | 0.8683 |
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+ | 0.1185 | 18.0 | 2196 | 0.3033 | 0.8922 | 0.8673 | 0.8763 | 0.8716 |
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+ | 0.1132 | 19.0 | 2318 | 0.3063 | 0.8897 | 0.8640 | 0.8745 | 0.8689 |
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+ | 0.1195 | 20.0 | 2440 | 0.3013 | 0.8922 | 0.8694 | 0.8712 | 0.8703 |
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  ### Framework versions
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