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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: 0.2929
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- - Accuracy: 0.8772
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- - Precision: 0.8592
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- - Recall: 0.8381
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- - F1: 0.8475
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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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- | 0.5594 | 1.0 | 122 | 0.5211 | 0.7268 | 0.6611 | 0.6292 | 0.6376 |
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- | 0.5065 | 2.0 | 244 | 0.5047 | 0.7419 | 0.6941 | 0.7074 | 0.6994 |
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- | 0.4577 | 3.0 | 366 | 0.4336 | 0.7945 | 0.7524 | 0.7446 | 0.7482 |
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- | 0.3996 | 4.0 | 488 | 0.3853 | 0.8321 | 0.8128 | 0.7637 | 0.7815 |
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- | 0.3611 | 5.0 | 610 | 0.3553 | 0.8496 | 0.8202 | 0.8136 | 0.8167 |
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- | 0.3333 | 6.0 | 732 | 0.3422 | 0.8496 | 0.8202 | 0.8136 | 0.8167 |
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- | 0.3085 | 7.0 | 854 | 0.3352 | 0.8596 | 0.8360 | 0.8182 | 0.8262 |
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- | 0.3104 | 8.0 | 976 | 0.3258 | 0.8622 | 0.8414 | 0.8175 | 0.8279 |
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- | 0.3015 | 9.0 | 1098 | 0.3172 | 0.8571 | 0.8289 | 0.8239 | 0.8264 |
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- | 0.2856 | 10.0 | 1220 | 0.3110 | 0.8596 | 0.8424 | 0.8082 | 0.8223 |
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- | 0.276 | 11.0 | 1342 | 0.3082 | 0.8672 | 0.8556 | 0.8135 | 0.8303 |
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- | 0.2772 | 12.0 | 1464 | 0.3043 | 0.8672 | 0.8393 | 0.8410 | 0.8402 |
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- | 0.2719 | 13.0 | 1586 | 0.3042 | 0.8722 | 0.8581 | 0.8246 | 0.8386 |
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- | 0.2595 | 14.0 | 1708 | 0.2963 | 0.8747 | 0.8537 | 0.8388 | 0.8457 |
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- | 0.2621 | 15.0 | 1830 | 0.2937 | 0.8772 | 0.8524 | 0.8506 | 0.8515 |
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- | 0.2653 | 16.0 | 1952 | 0.2935 | 0.8797 | 0.8572 | 0.8499 | 0.8534 |
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- | 0.2496 | 17.0 | 2074 | 0.2960 | 0.8822 | 0.8674 | 0.8417 | 0.8529 |
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- | 0.2579 | 18.0 | 2196 | 0.2939 | 0.8722 | 0.8512 | 0.8346 | 0.8422 |
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- | 0.2533 | 19.0 | 2318 | 0.2931 | 0.8772 | 0.8592 | 0.8381 | 0.8475 |
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- | 0.2429 | 20.0 | 2440 | 0.2929 | 0.8772 | 0.8592 | 0.8381 | 0.8475 |
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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: 0.2786
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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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  | 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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