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sentiment-lora-r8

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  1. README.md +25 -27
  2. sentiment-lora/pytorch_adapter.bin +1 -1
  3. 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: 0.2786
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- - Accuracy: 0.8847
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- - Precision: 0.8648
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- - Recall: 0.8534
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- - F1: 0.8588
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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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- | 0.5623 | 1.0 | 122 | 0.5217 | 0.7268 | 0.6604 | 0.6217 | 0.6301 |
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- | 0.5061 | 2.0 | 244 | 0.4898 | 0.7569 | 0.7074 | 0.7105 | 0.7089 |
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- | 0.4443 | 3.0 | 366 | 0.4085 | 0.8120 | 0.7751 | 0.7620 | 0.7679 |
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- | 0.3805 | 4.0 | 488 | 0.3672 | 0.8246 | 0.7980 | 0.7609 | 0.7752 |
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- | 0.3488 | 5.0 | 610 | 0.3535 | 0.8521 | 0.8207 | 0.8254 | 0.8229 |
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- | 0.3156 | 6.0 | 732 | 0.3337 | 0.8571 | 0.8299 | 0.8214 | 0.8255 |
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- | 0.3055 | 7.0 | 854 | 0.3217 | 0.8622 | 0.8385 | 0.8225 | 0.8298 |
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- | 0.2995 | 8.0 | 976 | 0.3145 | 0.8596 | 0.8347 | 0.8207 | 0.8272 |
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- | 0.2825 | 9.0 | 1098 | 0.3090 | 0.8672 | 0.8402 | 0.8385 | 0.8394 |
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- | 0.272 | 10.0 | 1220 | 0.2992 | 0.8722 | 0.8453 | 0.8471 | 0.8462 |
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- | 0.2626 | 11.0 | 1342 | 0.3008 | 0.8747 | 0.8568 | 0.8338 | 0.8440 |
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- | 0.2641 | 12.0 | 1464 | 0.2949 | 0.8747 | 0.8488 | 0.8488 | 0.8488 |
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- | 0.257 | 13.0 | 1586 | 0.2885 | 0.8772 | 0.8592 | 0.8381 | 0.8475 |
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- | 0.2473 | 14.0 | 1708 | 0.2826 | 0.8822 | 0.8596 | 0.8542 | 0.8568 |
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- | 0.2456 | 15.0 | 1830 | 0.2826 | 0.8847 | 0.8609 | 0.8609 | 0.8609 |
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- | 0.2477 | 16.0 | 1952 | 0.2795 | 0.8847 | 0.8621 | 0.8584 | 0.8602 |
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- | 0.2426 | 17.0 | 2074 | 0.2794 | 0.8797 | 0.8585 | 0.8474 | 0.8526 |
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- | 0.2359 | 18.0 | 2196 | 0.2796 | 0.8872 | 0.8658 | 0.8602 | 0.8629 |
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- | 0.2417 | 19.0 | 2318 | 0.2787 | 0.8847 | 0.8648 | 0.8534 | 0.8588 |
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- | 0.2319 | 20.0 | 2440 | 0.2786 | 0.8847 | 0.8648 | 0.8534 | 0.8588 |
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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: 0.2908
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+ - Accuracy: 0.8772
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+ - Precision: 0.8535
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+ - Recall: 0.8481
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+ - F1: 0.8507
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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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+ | 0.556 | 1.0 | 122 | 0.5325 | 0.7168 | 0.6617 | 0.6671 | 0.6641 |
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+ | 0.5103 | 2.0 | 244 | 0.4822 | 0.7719 | 0.7715 | 0.6386 | 0.6524 |
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+ | 0.4637 | 3.0 | 366 | 0.4245 | 0.8045 | 0.7715 | 0.7342 | 0.7480 |
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+ | 0.4173 | 4.0 | 488 | 0.3898 | 0.8246 | 0.7888 | 0.7859 | 0.7873 |
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+ | 0.3674 | 5.0 | 610 | 0.3571 | 0.8371 | 0.8059 | 0.7947 | 0.7999 |
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+ | 0.3484 | 6.0 | 732 | 0.3432 | 0.8371 | 0.8038 | 0.8022 | 0.8030 |
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+ | 0.3247 | 7.0 | 854 | 0.3299 | 0.8521 | 0.8271 | 0.8079 | 0.8164 |
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+ | 0.3102 | 8.0 | 976 | 0.3260 | 0.8622 | 0.8510 | 0.8050 | 0.8228 |
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+ | 0.2991 | 9.0 | 1098 | 0.3138 | 0.8571 | 0.8349 | 0.8114 | 0.8216 |
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+ | 0.29 | 10.0 | 1220 | 0.3123 | 0.8546 | 0.8324 | 0.8071 | 0.8180 |
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+ | 0.2778 | 11.0 | 1342 | 0.3065 | 0.8672 | 0.8423 | 0.8335 | 0.8377 |
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+ | 0.2702 | 12.0 | 1464 | 0.3006 | 0.8571 | 0.8349 | 0.8114 | 0.8216 |
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+ | 0.2664 | 13.0 | 1586 | 0.2996 | 0.8596 | 0.8316 | 0.8282 | 0.8298 |
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+ | 0.264 | 14.0 | 1708 | 0.2987 | 0.8722 | 0.8437 | 0.8521 | 0.8477 |
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+ | 0.254 | 15.0 | 1830 | 0.2951 | 0.8772 | 0.8514 | 0.8531 | 0.8522 |
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+ | 0.2571 | 16.0 | 1952 | 0.2945 | 0.8672 | 0.8463 | 0.8260 | 0.8351 |
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+ | 0.2511 | 17.0 | 2074 | 0.2918 | 0.8722 | 0.8463 | 0.8446 | 0.8454 |
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+ | 0.2574 | 18.0 | 2196 | 0.2909 | 0.8747 | 0.8510 | 0.8438 | 0.8473 |
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+ | 0.2508 | 19.0 | 2318 | 0.2907 | 0.8772 | 0.8535 | 0.8481 | 0.8507 |
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+ | 0.2536 | 20.0 | 2440 | 0.2908 | 0.8772 | 0.8535 | 0.8481 | 0.8507 |
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  ### Framework versions
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