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apwic
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nerui-base-2

Token Classification
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Safetensors
Indonesian
bert
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  1. README.md +115 -22
  2. model.safetensors +1 -1
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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:
@@ -17,23 +15,23 @@ 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: 0.0571
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- - Location Precision: 0.8812
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- - Location Recall: 0.9570
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- - Location F1: 0.9175
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  - Location Number: 93
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- - Organization Precision: 0.9130
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- - Organization Recall: 0.8855
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- - Organization F1: 0.8991
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  - Organization Number: 166
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- - Person Precision: 0.9786
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- - Person Recall: 0.9648
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- - Person F1: 0.9716
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  - Person Number: 142
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- - Overall Precision: 0.9279
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- - Overall Recall: 0.9302
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- - Overall F1: 0.9290
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- - Overall Accuracy: 0.9857
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  ## Model description
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@@ -58,17 +56,112 @@ The following hyperparameters were used during training:
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  - seed: 42
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
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- - num_epochs: 5.0
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Location Precision | Location Recall | Location F1 | Location Number | Organization Precision | Organization Recall | Organization F1 | Organization Number | Person Precision | Person Recall | Person F1 | Person Number | Overall Precision | Overall Recall | Overall F1 | Overall Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:------------------:|:---------------:|:-----------:|:---------------:|:----------------------:|:-------------------:|:---------------:|:-------------------:|:----------------:|:-------------:|:---------:|:-------------:|:-----------------:|:--------------:|:----------:|:----------------:|
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- | 0.2624 | 1.0 | 96 | 0.0635 | 0.7857 | 0.9462 | 0.8585 | 93 | 0.8545 | 0.8494 | 0.8520 | 166 | 0.9858 | 0.9789 | 0.9823 | 142 | 0.8804 | 0.9177 | 0.8987 | 0.9802 |
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- | 0.054 | 2.0 | 192 | 0.0530 | 0.8318 | 0.9570 | 0.89 | 93 | 0.8580 | 0.9096 | 0.8830 | 166 | 0.9787 | 0.9718 | 0.9753 | 142 | 0.8915 | 0.9426 | 0.9164 | 0.9841 |
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- | 0.0268 | 3.0 | 288 | 0.0673 | 0.8257 | 0.9677 | 0.8911 | 93 | 0.8869 | 0.8976 | 0.8922 | 166 | 0.9857 | 0.9718 | 0.9787 | 142 | 0.9041 | 0.9401 | 0.9218 | 0.9833 |
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- | 0.0159 | 4.0 | 384 | 0.0546 | 0.9167 | 0.9462 | 0.9312 | 93 | 0.8743 | 0.9217 | 0.8974 | 166 | 0.9786 | 0.9648 | 0.9716 | 142 | 0.9197 | 0.9426 | 0.9310 | 0.9868 |
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- | 0.0108 | 5.0 | 480 | 0.0571 | 0.8812 | 0.9570 | 0.9175 | 93 | 0.9130 | 0.8855 | 0.8991 | 166 | 0.9786 | 0.9648 | 0.9716 | 142 | 0.9279 | 0.9302 | 0.9290 | 0.9857 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions
 
1
  ---
 
 
2
  license: mit
3
  base_model: indolem/indobert-base-uncased
4
  tags:
 
15
 
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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.
17
  It achieves the following results on the evaluation set:
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+ - Loss: 0.1277
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+ - Location Precision: 0.9010
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+ - Location Recall: 0.9785
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+ - Location F1: 0.9381
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  - Location Number: 93
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+ - Organization Precision: 0.9441
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+ - Organization Recall: 0.9157
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+ - Organization F1: 0.9297
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  - Organization Number: 166
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+ - Person Precision: 0.9858
28
+ - Person Recall: 0.9789
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+ - Person F1: 0.9823
30
  - Person Number: 142
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+ - Overall Precision: 0.9479
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+ - Overall Recall: 0.9526
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+ - Overall F1: 0.9502
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+ - Overall Accuracy: 0.9890
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36
  ## Model description
37
 
 
56
  - seed: 42
57
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
58
  - lr_scheduler_type: linear
59
+ - num_epochs: 100.0
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61
  ### Training results
62
 
63
  | Training Loss | Epoch | Step | Validation Loss | Location Precision | Location Recall | Location F1 | Location Number | Organization Precision | Organization Recall | Organization F1 | Organization Number | Person Precision | Person Recall | Person F1 | Person Number | Overall Precision | Overall Recall | Overall F1 | Overall Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:------------------:|:---------------:|:-----------:|:---------------:|:----------------------:|:-------------------:|:---------------:|:-------------------:|:----------------:|:-------------:|:---------:|:-------------:|:-----------------:|:--------------:|:----------:|:----------------:|
65
+ | 0.2536 | 1.0 | 96 | 0.0625 | 0.7857 | 0.9462 | 0.8585 | 93 | 0.8675 | 0.7892 | 0.8265 | 166 | 0.9718 | 0.9718 | 0.9718 | 142 | 0.8815 | 0.8903 | 0.8859 | 0.9781 |
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+ | 0.0547 | 2.0 | 192 | 0.0541 | 0.8241 | 0.9570 | 0.8856 | 93 | 0.9363 | 0.8855 | 0.9102 | 166 | 0.9716 | 0.9648 | 0.9682 | 142 | 0.9187 | 0.9302 | 0.9244 | 0.9841 |
67
+ | 0.032 | 3.0 | 288 | 0.0712 | 0.8824 | 0.9677 | 0.9231 | 93 | 0.9299 | 0.8795 | 0.9040 | 166 | 0.9787 | 0.9718 | 0.9753 | 142 | 0.935 | 0.9327 | 0.9338 | 0.9849 |
68
+ | 0.0196 | 4.0 | 384 | 0.0573 | 0.9341 | 0.9140 | 0.9239 | 93 | 0.9176 | 0.9398 | 0.9286 | 166 | 0.9858 | 0.9789 | 0.9823 | 142 | 0.9453 | 0.9476 | 0.9465 | 0.9879 |
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+ | 0.0114 | 5.0 | 480 | 0.0701 | 0.8687 | 0.9247 | 0.8958 | 93 | 0.9096 | 0.9096 | 0.9096 | 166 | 0.9716 | 0.9648 | 0.9682 | 142 | 0.9212 | 0.9327 | 0.9269 | 0.9863 |
70
+ | 0.0098 | 6.0 | 576 | 0.1047 | 0.7909 | 0.9355 | 0.8571 | 93 | 0.9205 | 0.8373 | 0.8770 | 166 | 0.9787 | 0.9718 | 0.9753 | 142 | 0.9055 | 0.9077 | 0.9066 | 0.9794 |
71
+ | 0.0096 | 7.0 | 672 | 0.0745 | 0.8544 | 0.9462 | 0.8980 | 93 | 0.9477 | 0.8735 | 0.9091 | 166 | 0.9718 | 0.9718 | 0.9718 | 142 | 0.9322 | 0.9252 | 0.9287 | 0.9874 |
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+ | 0.0088 | 8.0 | 768 | 0.0767 | 0.8365 | 0.9355 | 0.8832 | 93 | 0.925 | 0.8916 | 0.9080 | 166 | 0.9857 | 0.9718 | 0.9787 | 142 | 0.9233 | 0.9302 | 0.9267 | 0.9871 |
73
+ | 0.007 | 9.0 | 864 | 0.0843 | 0.8476 | 0.9570 | 0.8990 | 93 | 0.9308 | 0.8916 | 0.9108 | 166 | 0.9718 | 0.9718 | 0.9718 | 142 | 0.9236 | 0.9352 | 0.9294 | 0.9855 |
74
+ | 0.0073 | 10.0 | 960 | 0.0833 | 0.8571 | 0.9677 | 0.9091 | 93 | 0.9187 | 0.8855 | 0.9018 | 166 | 0.9718 | 0.9718 | 0.9718 | 142 | 0.9214 | 0.9352 | 0.9282 | 0.9866 |
75
+ | 0.0044 | 11.0 | 1056 | 0.0729 | 0.9043 | 0.9140 | 0.9091 | 93 | 0.9557 | 0.9096 | 0.9321 | 166 | 0.9789 | 0.9789 | 0.9789 | 142 | 0.9518 | 0.9352 | 0.9434 | 0.9877 |
76
+ | 0.0049 | 12.0 | 1152 | 0.0789 | 0.8614 | 0.9355 | 0.8969 | 93 | 0.9441 | 0.9157 | 0.9297 | 166 | 0.9787 | 0.9718 | 0.9753 | 142 | 0.9355 | 0.9401 | 0.9378 | 0.9879 |
77
+ | 0.0034 | 13.0 | 1248 | 0.0764 | 0.8980 | 0.9462 | 0.9215 | 93 | 0.9387 | 0.9217 | 0.9301 | 166 | 0.9787 | 0.9718 | 0.9753 | 142 | 0.9428 | 0.9451 | 0.9440 | 0.9888 |
78
+ | 0.0026 | 14.0 | 1344 | 0.0846 | 0.88 | 0.9462 | 0.9119 | 93 | 0.9264 | 0.9096 | 0.9179 | 166 | 0.9856 | 0.9648 | 0.9751 | 142 | 0.9353 | 0.9377 | 0.9365 | 0.9860 |
79
+ | 0.0047 | 15.0 | 1440 | 0.0882 | 0.8641 | 0.9570 | 0.9082 | 93 | 0.9193 | 0.8916 | 0.9052 | 166 | 0.9514 | 0.9648 | 0.9580 | 142 | 0.9167 | 0.9327 | 0.9246 | 0.9863 |
80
+ | 0.0034 | 16.0 | 1536 | 0.0855 | 0.8854 | 0.9140 | 0.8995 | 93 | 0.9325 | 0.9157 | 0.9240 | 166 | 0.9787 | 0.9718 | 0.9753 | 142 | 0.9375 | 0.9352 | 0.9363 | 0.9879 |
81
+ | 0.0036 | 17.0 | 1632 | 0.0843 | 0.9362 | 0.9462 | 0.9412 | 93 | 0.8947 | 0.9217 | 0.9080 | 166 | 0.9718 | 0.9718 | 0.9718 | 142 | 0.9312 | 0.9451 | 0.9381 | 0.9860 |
82
+ | 0.0022 | 18.0 | 1728 | 0.0984 | 0.8725 | 0.9570 | 0.9128 | 93 | 0.9308 | 0.8916 | 0.9108 | 166 | 0.9857 | 0.9718 | 0.9787 | 142 | 0.9352 | 0.9352 | 0.9352 | 0.9863 |
83
+ | 0.0038 | 19.0 | 1824 | 0.0893 | 0.8544 | 0.9462 | 0.8980 | 93 | 0.9434 | 0.9036 | 0.9231 | 166 | 0.9858 | 0.9789 | 0.9823 | 142 | 0.9355 | 0.9401 | 0.9378 | 0.9874 |
84
+ | 0.0023 | 20.0 | 1920 | 0.0831 | 0.8788 | 0.9355 | 0.9062 | 93 | 0.9444 | 0.9217 | 0.9329 | 166 | 0.9856 | 0.9648 | 0.9751 | 142 | 0.9425 | 0.9401 | 0.9413 | 0.9885 |
85
+ | 0.0018 | 21.0 | 2016 | 0.0857 | 0.9263 | 0.9462 | 0.9362 | 93 | 0.9080 | 0.9518 | 0.9294 | 166 | 0.9580 | 0.9648 | 0.9614 | 142 | 0.9296 | 0.9551 | 0.9422 | 0.9874 |
86
+ | 0.0024 | 22.0 | 2112 | 0.0915 | 0.88 | 0.9462 | 0.9119 | 93 | 0.9212 | 0.9157 | 0.9184 | 166 | 0.9856 | 0.9648 | 0.9751 | 142 | 0.9332 | 0.9401 | 0.9366 | 0.9879 |
87
+ | 0.0015 | 23.0 | 2208 | 0.0881 | 0.8725 | 0.9570 | 0.9128 | 93 | 0.9321 | 0.9096 | 0.9207 | 166 | 0.9650 | 0.9718 | 0.9684 | 142 | 0.9287 | 0.9426 | 0.9356 | 0.9877 |
88
+ | 0.0019 | 24.0 | 2304 | 0.0875 | 0.89 | 0.9570 | 0.9223 | 93 | 0.95 | 0.9157 | 0.9325 | 166 | 0.9857 | 0.9718 | 0.9787 | 142 | 0.9475 | 0.9451 | 0.9463 | 0.9893 |
89
+ | 0.001 | 25.0 | 2400 | 0.0976 | 0.8812 | 0.9570 | 0.9175 | 93 | 0.9554 | 0.9036 | 0.9288 | 166 | 0.9718 | 0.9718 | 0.9718 | 142 | 0.9425 | 0.9401 | 0.9413 | 0.9882 |
90
+ | 0.003 | 26.0 | 2496 | 0.0855 | 0.8627 | 0.9462 | 0.9026 | 93 | 0.9259 | 0.9036 | 0.9146 | 166 | 0.9787 | 0.9718 | 0.9753 | 142 | 0.9284 | 0.9377 | 0.9330 | 0.9868 |
91
+ | 0.0016 | 27.0 | 2592 | 0.0964 | 0.8641 | 0.9570 | 0.9082 | 93 | 0.9255 | 0.8976 | 0.9113 | 166 | 0.9787 | 0.9718 | 0.9753 | 142 | 0.9284 | 0.9377 | 0.9330 | 0.9874 |
92
+ | 0.002 | 28.0 | 2688 | 0.0986 | 0.88 | 0.9462 | 0.9119 | 93 | 0.9264 | 0.9096 | 0.9179 | 166 | 0.9857 | 0.9718 | 0.9787 | 142 | 0.9355 | 0.9401 | 0.9378 | 0.9874 |
93
+ | 0.0022 | 29.0 | 2784 | 0.0979 | 0.8980 | 0.9462 | 0.9215 | 93 | 0.9375 | 0.9036 | 0.9202 | 166 | 0.9787 | 0.9718 | 0.9753 | 142 | 0.9424 | 0.9377 | 0.94 | 0.9888 |
94
+ | 0.0021 | 30.0 | 2880 | 0.0972 | 0.9082 | 0.9570 | 0.9319 | 93 | 0.9329 | 0.9217 | 0.9273 | 166 | 0.9858 | 0.9789 | 0.9823 | 142 | 0.9454 | 0.9501 | 0.9478 | 0.9888 |
95
+ | 0.0017 | 31.0 | 2976 | 0.1149 | 0.8911 | 0.9677 | 0.9278 | 93 | 0.9441 | 0.9157 | 0.9297 | 166 | 0.9718 | 0.9718 | 0.9718 | 142 | 0.9406 | 0.9476 | 0.9441 | 0.9877 |
96
+ | 0.0016 | 32.0 | 3072 | 0.0968 | 0.88 | 0.9462 | 0.9119 | 93 | 0.9441 | 0.9157 | 0.9297 | 166 | 0.9857 | 0.9718 | 0.9787 | 142 | 0.9426 | 0.9426 | 0.9426 | 0.9885 |
97
+ | 0.0011 | 33.0 | 3168 | 0.0888 | 0.8969 | 0.9355 | 0.9158 | 93 | 0.9387 | 0.9217 | 0.9301 | 166 | 0.9787 | 0.9718 | 0.9753 | 142 | 0.9426 | 0.9426 | 0.9426 | 0.9893 |
98
+ | 0.0018 | 34.0 | 3264 | 0.0898 | 0.8911 | 0.9677 | 0.9278 | 93 | 0.9444 | 0.9217 | 0.9329 | 166 | 0.9720 | 0.9789 | 0.9754 | 142 | 0.9409 | 0.9526 | 0.9467 | 0.9888 |
99
+ | 0.0008 | 35.0 | 3360 | 0.0988 | 0.8835 | 0.9785 | 0.9286 | 93 | 0.9437 | 0.9096 | 0.9264 | 166 | 0.9858 | 0.9789 | 0.9823 | 142 | 0.9431 | 0.9501 | 0.9466 | 0.9890 |
100
+ | 0.0025 | 36.0 | 3456 | 0.0905 | 0.8476 | 0.9570 | 0.8990 | 93 | 0.95 | 0.9157 | 0.9325 | 166 | 0.9720 | 0.9789 | 0.9754 | 142 | 0.9314 | 0.9476 | 0.9394 | 0.9885 |
101
+ | 0.0023 | 37.0 | 3552 | 0.0926 | 0.9082 | 0.9570 | 0.9319 | 93 | 0.9506 | 0.9277 | 0.9390 | 166 | 0.9789 | 0.9789 | 0.9789 | 142 | 0.9502 | 0.9526 | 0.9514 | 0.9890 |
102
+ | 0.0019 | 38.0 | 3648 | 0.1043 | 0.9167 | 0.9462 | 0.9312 | 93 | 0.9176 | 0.9398 | 0.9286 | 166 | 0.9787 | 0.9718 | 0.9753 | 142 | 0.9386 | 0.9526 | 0.9455 | 0.9879 |
103
+ | 0.0016 | 39.0 | 3744 | 0.1011 | 0.9091 | 0.9677 | 0.9375 | 93 | 0.9441 | 0.9157 | 0.9297 | 166 | 0.9653 | 0.9789 | 0.9720 | 142 | 0.9431 | 0.9501 | 0.9466 | 0.9879 |
104
+ | 0.0017 | 40.0 | 3840 | 0.1100 | 0.8713 | 0.9462 | 0.9072 | 93 | 0.9375 | 0.9036 | 0.9202 | 166 | 0.9650 | 0.9718 | 0.9684 | 142 | 0.9307 | 0.9377 | 0.9342 | 0.9868 |
105
+ | 0.0014 | 41.0 | 3936 | 0.1257 | 0.8812 | 0.9570 | 0.9175 | 93 | 0.8982 | 0.9036 | 0.9009 | 166 | 0.9786 | 0.9648 | 0.9716 | 142 | 0.9216 | 0.9377 | 0.9295 | 0.9852 |
106
+ | 0.0021 | 42.0 | 4032 | 0.1077 | 0.8911 | 0.9677 | 0.9278 | 93 | 0.9490 | 0.8976 | 0.9226 | 166 | 0.9720 | 0.9789 | 0.9754 | 142 | 0.9426 | 0.9426 | 0.9426 | 0.9885 |
107
+ | 0.0026 | 43.0 | 4128 | 0.1268 | 0.8725 | 0.9570 | 0.9128 | 93 | 0.9141 | 0.8976 | 0.9058 | 166 | 0.9650 | 0.9718 | 0.9684 | 142 | 0.9216 | 0.9377 | 0.9295 | 0.9838 |
108
+ | 0.0016 | 44.0 | 4224 | 0.1105 | 0.8824 | 0.9677 | 0.9231 | 93 | 0.9677 | 0.9036 | 0.9346 | 166 | 0.9648 | 0.9648 | 0.9648 | 142 | 0.9449 | 0.9401 | 0.9425 | 0.9866 |
109
+ | 0.0013 | 45.0 | 4320 | 0.1288 | 0.89 | 0.9570 | 0.9223 | 93 | 0.9157 | 0.9157 | 0.9157 | 166 | 0.9718 | 0.9718 | 0.9718 | 142 | 0.9289 | 0.9451 | 0.9370 | 0.9849 |
110
+ | 0.0014 | 46.0 | 4416 | 0.1480 | 0.8889 | 0.9462 | 0.9167 | 93 | 0.8935 | 0.9096 | 0.9015 | 166 | 0.9444 | 0.9577 | 0.9510 | 142 | 0.9102 | 0.9352 | 0.9225 | 0.9822 |
111
+ | 0.0013 | 47.0 | 4512 | 0.1075 | 0.8911 | 0.9677 | 0.9278 | 93 | 0.95 | 0.9157 | 0.9325 | 166 | 0.9857 | 0.9718 | 0.9787 | 142 | 0.9476 | 0.9476 | 0.9476 | 0.9890 |
112
+ | 0.0008 | 48.0 | 4608 | 0.1144 | 0.89 | 0.9570 | 0.9223 | 93 | 0.9313 | 0.8976 | 0.9141 | 166 | 0.9786 | 0.9648 | 0.9716 | 142 | 0.9375 | 0.9352 | 0.9363 | 0.9868 |
113
+ | 0.0016 | 49.0 | 4704 | 0.1204 | 0.8824 | 0.9677 | 0.9231 | 93 | 0.9557 | 0.9096 | 0.9321 | 166 | 0.9787 | 0.9718 | 0.9753 | 142 | 0.9451 | 0.9451 | 0.9451 | 0.9871 |
114
+ | 0.0018 | 50.0 | 4800 | 0.1150 | 0.8824 | 0.9677 | 0.9231 | 93 | 0.9379 | 0.9096 | 0.9235 | 166 | 0.9857 | 0.9718 | 0.9787 | 142 | 0.9404 | 0.9451 | 0.9428 | 0.9874 |
115
+ | 0.0008 | 51.0 | 4896 | 0.1182 | 0.8812 | 0.9570 | 0.9175 | 93 | 0.9563 | 0.9217 | 0.9387 | 166 | 0.9787 | 0.9718 | 0.9753 | 142 | 0.9453 | 0.9476 | 0.9465 | 0.9882 |
116
+ | 0.0009 | 52.0 | 4992 | 0.1180 | 0.8911 | 0.9677 | 0.9278 | 93 | 0.9444 | 0.9217 | 0.9329 | 166 | 0.9857 | 0.9718 | 0.9787 | 142 | 0.9454 | 0.9501 | 0.9478 | 0.9885 |
117
+ | 0.0013 | 53.0 | 5088 | 0.1120 | 0.9082 | 0.9570 | 0.9319 | 93 | 0.9387 | 0.9217 | 0.9301 | 166 | 0.9787 | 0.9718 | 0.9753 | 142 | 0.9453 | 0.9476 | 0.9465 | 0.9885 |
118
+ | 0.0004 | 54.0 | 5184 | 0.1303 | 0.8812 | 0.9570 | 0.9175 | 93 | 0.9162 | 0.9217 | 0.9189 | 166 | 0.9718 | 0.9718 | 0.9718 | 142 | 0.9268 | 0.9476 | 0.9371 | 0.9855 |
119
+ | 0.0005 | 55.0 | 5280 | 0.1208 | 0.91 | 0.9785 | 0.9430 | 93 | 0.9444 | 0.9217 | 0.9329 | 166 | 0.9653 | 0.9789 | 0.9720 | 142 | 0.9433 | 0.9551 | 0.9492 | 0.9868 |
120
+ | 0.0006 | 56.0 | 5376 | 0.1206 | 0.9 | 0.9677 | 0.9326 | 93 | 0.9565 | 0.9277 | 0.9419 | 166 | 0.9718 | 0.9718 | 0.9718 | 142 | 0.9479 | 0.9526 | 0.9502 | 0.9888 |
121
+ | 0.0009 | 57.0 | 5472 | 0.1302 | 0.8824 | 0.9677 | 0.9231 | 93 | 0.9563 | 0.9217 | 0.9387 | 166 | 0.9650 | 0.9718 | 0.9684 | 142 | 0.9407 | 0.9501 | 0.9454 | 0.9879 |
122
+ | 0.0005 | 58.0 | 5568 | 0.1179 | 0.8824 | 0.9677 | 0.9231 | 93 | 0.9563 | 0.9217 | 0.9387 | 166 | 0.9787 | 0.9718 | 0.9753 | 142 | 0.9454 | 0.9501 | 0.9478 | 0.9888 |
123
+ | 0.0007 | 59.0 | 5664 | 0.1299 | 0.8812 | 0.9570 | 0.9175 | 93 | 0.9560 | 0.9157 | 0.9354 | 166 | 0.9714 | 0.9577 | 0.9645 | 142 | 0.9425 | 0.9401 | 0.9413 | 0.9879 |
124
+ | 0.0023 | 60.0 | 5760 | 0.1023 | 0.8922 | 0.9785 | 0.9333 | 93 | 0.9682 | 0.9157 | 0.9412 | 166 | 0.9586 | 0.9789 | 0.9686 | 142 | 0.9455 | 0.9526 | 0.9491 | 0.9888 |
125
+ | 0.0003 | 61.0 | 5856 | 0.1088 | 0.9010 | 0.9785 | 0.9381 | 93 | 0.9744 | 0.9157 | 0.9441 | 166 | 0.9857 | 0.9718 | 0.9787 | 142 | 0.9597 | 0.9501 | 0.9549 | 0.9901 |
126
+ | 0.0002 | 62.0 | 5952 | 0.1148 | 0.9 | 0.9677 | 0.9326 | 93 | 0.9560 | 0.9157 | 0.9354 | 166 | 0.9858 | 0.9789 | 0.9823 | 142 | 0.9525 | 0.9501 | 0.9513 | 0.9896 |
127
+ | 0.0005 | 63.0 | 6048 | 0.1234 | 0.9010 | 0.9785 | 0.9381 | 93 | 0.9444 | 0.9217 | 0.9329 | 166 | 0.9858 | 0.9789 | 0.9823 | 142 | 0.9480 | 0.9551 | 0.9516 | 0.9888 |
128
+ | 0.0004 | 64.0 | 6144 | 0.1111 | 0.8812 | 0.9570 | 0.9175 | 93 | 0.9682 | 0.9157 | 0.9412 | 166 | 0.9856 | 0.9648 | 0.9751 | 142 | 0.9521 | 0.9426 | 0.9474 | 0.9893 |
129
+ | 0.0004 | 65.0 | 6240 | 0.1186 | 0.9 | 0.9677 | 0.9326 | 93 | 0.9448 | 0.9277 | 0.9362 | 166 | 0.9786 | 0.9648 | 0.9716 | 142 | 0.9454 | 0.9501 | 0.9478 | 0.9885 |
130
+ | 0.0003 | 66.0 | 6336 | 0.1187 | 0.9 | 0.9677 | 0.9326 | 93 | 0.9623 | 0.9217 | 0.9415 | 166 | 0.9856 | 0.9648 | 0.9751 | 142 | 0.9548 | 0.9476 | 0.9512 | 0.9896 |
131
+ | 0.0003 | 67.0 | 6432 | 0.1245 | 0.8990 | 0.9570 | 0.9271 | 93 | 0.9441 | 0.9157 | 0.9297 | 166 | 0.9856 | 0.9648 | 0.9751 | 142 | 0.9474 | 0.9426 | 0.9450 | 0.9888 |
132
+ | 0.0006 | 68.0 | 6528 | 0.1209 | 0.8990 | 0.9570 | 0.9271 | 93 | 0.95 | 0.9157 | 0.9325 | 166 | 0.9856 | 0.9648 | 0.9751 | 142 | 0.9497 | 0.9426 | 0.9462 | 0.9890 |
133
+ | 0.0003 | 69.0 | 6624 | 0.1199 | 0.8990 | 0.9570 | 0.9271 | 93 | 0.9441 | 0.9157 | 0.9297 | 166 | 0.9786 | 0.9648 | 0.9716 | 142 | 0.945 | 0.9426 | 0.9438 | 0.9882 |
134
+ | 0.0003 | 70.0 | 6720 | 0.1195 | 0.8812 | 0.9570 | 0.9175 | 93 | 0.9560 | 0.9157 | 0.9354 | 166 | 0.9856 | 0.9648 | 0.9751 | 142 | 0.9474 | 0.9426 | 0.9450 | 0.9888 |
135
+ | 0.0006 | 71.0 | 6816 | 0.1209 | 0.8812 | 0.9570 | 0.9175 | 93 | 0.9620 | 0.9157 | 0.9383 | 166 | 0.9856 | 0.9648 | 0.9751 | 142 | 0.9497 | 0.9426 | 0.9462 | 0.9888 |
136
+ | 0.0003 | 72.0 | 6912 | 0.1284 | 0.8911 | 0.9677 | 0.9278 | 93 | 0.9497 | 0.9096 | 0.9292 | 166 | 0.9856 | 0.9648 | 0.9751 | 142 | 0.9474 | 0.9426 | 0.9450 | 0.9882 |
137
+ | 0.0007 | 73.0 | 7008 | 0.1271 | 0.8824 | 0.9677 | 0.9231 | 93 | 0.9444 | 0.9217 | 0.9329 | 166 | 0.9856 | 0.9648 | 0.9751 | 142 | 0.9429 | 0.9476 | 0.9453 | 0.9879 |
138
+ | 0.0006 | 74.0 | 7104 | 0.1311 | 0.89 | 0.9570 | 0.9223 | 93 | 0.9560 | 0.9157 | 0.9354 | 166 | 0.9856 | 0.9648 | 0.9751 | 142 | 0.9497 | 0.9426 | 0.9462 | 0.9890 |
139
+ | 0.0012 | 75.0 | 7200 | 0.1237 | 0.8911 | 0.9677 | 0.9278 | 93 | 0.9620 | 0.9157 | 0.9383 | 166 | 0.9856 | 0.9648 | 0.9751 | 142 | 0.9523 | 0.9451 | 0.9487 | 0.9893 |
140
+ | 0.001 | 76.0 | 7296 | 0.1214 | 0.8824 | 0.9677 | 0.9231 | 93 | 0.9677 | 0.9036 | 0.9346 | 166 | 0.9856 | 0.9648 | 0.9751 | 142 | 0.9520 | 0.9401 | 0.9460 | 0.9890 |
141
+ | 0.0003 | 77.0 | 7392 | 0.1177 | 0.8911 | 0.9677 | 0.9278 | 93 | 0.9444 | 0.9217 | 0.9329 | 166 | 0.9857 | 0.9718 | 0.9787 | 142 | 0.9454 | 0.9501 | 0.9478 | 0.9885 |
142
+ | 0.0005 | 78.0 | 7488 | 0.1234 | 0.8911 | 0.9677 | 0.9278 | 93 | 0.9506 | 0.9277 | 0.9390 | 166 | 0.9856 | 0.9648 | 0.9751 | 142 | 0.9478 | 0.9501 | 0.9489 | 0.9885 |
143
+ | 0.0018 | 79.0 | 7584 | 0.1135 | 0.8990 | 0.9570 | 0.9271 | 93 | 0.9451 | 0.9337 | 0.9394 | 166 | 0.9857 | 0.9718 | 0.9787 | 142 | 0.9479 | 0.9526 | 0.9502 | 0.9893 |
144
+ | 0.0004 | 80.0 | 7680 | 0.1213 | 0.8911 | 0.9677 | 0.9278 | 93 | 0.95 | 0.9157 | 0.9325 | 166 | 0.9857 | 0.9718 | 0.9787 | 142 | 0.9476 | 0.9476 | 0.9476 | 0.9890 |
145
+ | 0.0002 | 81.0 | 7776 | 0.1281 | 0.8824 | 0.9677 | 0.9231 | 93 | 0.9557 | 0.9096 | 0.9321 | 166 | 0.9857 | 0.9718 | 0.9787 | 142 | 0.9475 | 0.9451 | 0.9463 | 0.9888 |
146
+ | 0.0007 | 82.0 | 7872 | 0.1166 | 0.9091 | 0.9677 | 0.9375 | 93 | 0.9506 | 0.9277 | 0.9390 | 166 | 0.9857 | 0.9718 | 0.9787 | 142 | 0.9526 | 0.9526 | 0.9526 | 0.9896 |
147
+ | 0.0004 | 83.0 | 7968 | 0.1387 | 0.8654 | 0.9677 | 0.9137 | 93 | 0.9379 | 0.9096 | 0.9235 | 166 | 0.9857 | 0.9718 | 0.9787 | 142 | 0.9358 | 0.9451 | 0.9404 | 0.9874 |
148
+ | 0.0002 | 84.0 | 8064 | 0.1367 | 0.8738 | 0.9677 | 0.9184 | 93 | 0.9497 | 0.9096 | 0.9292 | 166 | 0.9857 | 0.9718 | 0.9787 | 142 | 0.9428 | 0.9451 | 0.9440 | 0.9885 |
149
+ | 0.0007 | 85.0 | 8160 | 0.1287 | 0.8922 | 0.9785 | 0.9333 | 93 | 0.9497 | 0.9096 | 0.9292 | 166 | 0.9857 | 0.9718 | 0.9787 | 142 | 0.9476 | 0.9476 | 0.9476 | 0.9888 |
150
+ | 0.0008 | 86.0 | 8256 | 0.1281 | 0.8922 | 0.9785 | 0.9333 | 93 | 0.9437 | 0.9096 | 0.9264 | 166 | 0.9858 | 0.9789 | 0.9823 | 142 | 0.9454 | 0.9501 | 0.9478 | 0.9888 |
151
+ | 0.0002 | 87.0 | 8352 | 0.1266 | 0.8922 | 0.9785 | 0.9333 | 93 | 0.9497 | 0.9096 | 0.9292 | 166 | 0.9857 | 0.9718 | 0.9787 | 142 | 0.9476 | 0.9476 | 0.9476 | 0.9888 |
152
+ | 0.0005 | 88.0 | 8448 | 0.1273 | 0.8922 | 0.9785 | 0.9333 | 93 | 0.9557 | 0.9096 | 0.9321 | 166 | 0.9857 | 0.9718 | 0.9787 | 142 | 0.95 | 0.9476 | 0.9488 | 0.9890 |
153
+ | 0.0003 | 89.0 | 8544 | 0.1263 | 0.9010 | 0.9785 | 0.9381 | 93 | 0.9560 | 0.9157 | 0.9354 | 166 | 0.9857 | 0.9718 | 0.9787 | 142 | 0.9525 | 0.9501 | 0.9513 | 0.9893 |
154
+ | 0.0001 | 90.0 | 8640 | 0.1265 | 0.9010 | 0.9785 | 0.9381 | 93 | 0.95 | 0.9157 | 0.9325 | 166 | 0.9857 | 0.9718 | 0.9787 | 142 | 0.9501 | 0.9501 | 0.9501 | 0.9890 |
155
+ | 0.0002 | 91.0 | 8736 | 0.1269 | 0.9010 | 0.9785 | 0.9381 | 93 | 0.95 | 0.9157 | 0.9325 | 166 | 0.9857 | 0.9718 | 0.9787 | 142 | 0.9501 | 0.9501 | 0.9501 | 0.9890 |
156
+ | 0.0001 | 92.0 | 8832 | 0.1283 | 0.9010 | 0.9785 | 0.9381 | 93 | 0.9441 | 0.9157 | 0.9297 | 166 | 0.9858 | 0.9789 | 0.9823 | 142 | 0.9479 | 0.9526 | 0.9502 | 0.9890 |
157
+ | 0.0002 | 93.0 | 8928 | 0.1284 | 0.9010 | 0.9785 | 0.9381 | 93 | 0.9441 | 0.9157 | 0.9297 | 166 | 0.9858 | 0.9789 | 0.9823 | 142 | 0.9479 | 0.9526 | 0.9502 | 0.9890 |
158
+ | 0.0002 | 94.0 | 9024 | 0.1286 | 0.9010 | 0.9785 | 0.9381 | 93 | 0.9441 | 0.9157 | 0.9297 | 166 | 0.9858 | 0.9789 | 0.9823 | 142 | 0.9479 | 0.9526 | 0.9502 | 0.9890 |
159
+ | 0.0002 | 95.0 | 9120 | 0.1288 | 0.9010 | 0.9785 | 0.9381 | 93 | 0.9441 | 0.9157 | 0.9297 | 166 | 0.9858 | 0.9789 | 0.9823 | 142 | 0.9479 | 0.9526 | 0.9502 | 0.9890 |
160
+ | 0.0002 | 96.0 | 9216 | 0.1285 | 0.9010 | 0.9785 | 0.9381 | 93 | 0.9441 | 0.9157 | 0.9297 | 166 | 0.9858 | 0.9789 | 0.9823 | 142 | 0.9479 | 0.9526 | 0.9502 | 0.9890 |
161
+ | 0.0002 | 97.0 | 9312 | 0.1286 | 0.9010 | 0.9785 | 0.9381 | 93 | 0.9441 | 0.9157 | 0.9297 | 166 | 0.9858 | 0.9789 | 0.9823 | 142 | 0.9479 | 0.9526 | 0.9502 | 0.9890 |
162
+ | 0.0005 | 98.0 | 9408 | 0.1277 | 0.9010 | 0.9785 | 0.9381 | 93 | 0.9441 | 0.9157 | 0.9297 | 166 | 0.9858 | 0.9789 | 0.9823 | 142 | 0.9479 | 0.9526 | 0.9502 | 0.9890 |
163
+ | 0.0004 | 99.0 | 9504 | 0.1276 | 0.9010 | 0.9785 | 0.9381 | 93 | 0.9441 | 0.9157 | 0.9297 | 166 | 0.9858 | 0.9789 | 0.9823 | 142 | 0.9479 | 0.9526 | 0.9502 | 0.9890 |
164
+ | 0.0003 | 100.0 | 9600 | 0.1277 | 0.9010 | 0.9785 | 0.9381 | 93 | 0.9441 | 0.9157 | 0.9297 | 166 | 0.9858 | 0.9789 | 0.9823 | 142 | 0.9479 | 0.9526 | 0.9502 | 0.9890 |
165
 
166
 
167
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