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arabert_cross_organization_task4_fold2

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  1. README.md +95 -90
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@@ -3,20 +3,20 @@ base_model: aubmindlab/bert-base-arabertv02
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  tags:
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  - generated_from_trainer
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  model-index:
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- - name: arabert_cross_organization_task4_fold1
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  results: []
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  ---
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  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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  should probably proofread and complete it, then remove this comment. -->
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- # arabert_cross_organization_task4_fold1
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  This model is a fine-tuned version of [aubmindlab/bert-base-arabertv02](https://huggingface.co/aubmindlab/bert-base-arabertv02) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.7438
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- - Qwk: 0.4143
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- - Mse: 0.7438
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  ## Model description
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@@ -47,91 +47,96 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Qwk | Mse |
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  |:-------------:|:------:|:----:|:---------------:|:-------:|:------:|
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- | No log | 0.1176 | 2 | 3.2005 | 0.0155 | 3.2005 |
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- | No log | 0.2353 | 4 | 1.7053 | -0.0034 | 1.7053 |
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- | No log | 0.3529 | 6 | 1.1027 | 0.1636 | 1.1027 |
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- | No log | 0.4706 | 8 | 1.0959 | 0.1953 | 1.0959 |
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- | No log | 0.5882 | 10 | 1.1008 | 0.2356 | 1.1008 |
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- | No log | 0.7059 | 12 | 0.7123 | 0.3763 | 0.7123 |
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- | No log | 0.8235 | 14 | 0.7466 | 0.4020 | 0.7466 |
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- | No log | 0.9412 | 16 | 0.9174 | 0.3522 | 0.9174 |
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- | No log | 1.0588 | 18 | 0.9416 | 0.3154 | 0.9416 |
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- | No log | 1.1765 | 20 | 0.7002 | 0.3766 | 0.7002 |
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- | No log | 1.2941 | 22 | 0.6826 | 0.3709 | 0.6826 |
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- | No log | 1.4118 | 24 | 0.6996 | 0.3822 | 0.6996 |
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- | No log | 1.5294 | 26 | 0.6165 | 0.4733 | 0.6165 |
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- | No log | 1.6471 | 28 | 0.5696 | 0.5228 | 0.5696 |
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- | No log | 1.7647 | 30 | 0.7076 | 0.4534 | 0.7076 |
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- | No log | 1.8824 | 32 | 0.7251 | 0.4533 | 0.7251 |
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- | No log | 2.0 | 34 | 0.5922 | 0.4921 | 0.5922 |
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- | No log | 2.1176 | 36 | 0.5428 | 0.5484 | 0.5428 |
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- | No log | 2.2353 | 38 | 0.5662 | 0.5159 | 0.5662 |
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- | No log | 2.3529 | 40 | 0.6256 | 0.4714 | 0.6256 |
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- | No log | 2.4706 | 42 | 0.6008 | 0.4805 | 0.6008 |
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- | No log | 2.5882 | 44 | 0.5493 | 0.5367 | 0.5493 |
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- | No log | 2.7059 | 46 | 0.5855 | 0.5042 | 0.5855 |
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- | No log | 2.8235 | 48 | 0.6888 | 0.4526 | 0.6888 |
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- | No log | 2.9412 | 50 | 0.6594 | 0.4838 | 0.6594 |
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- | No log | 3.0588 | 52 | 0.5913 | 0.5174 | 0.5913 |
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- | No log | 3.1765 | 54 | 0.5440 | 0.5485 | 0.5440 |
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- | No log | 3.2941 | 56 | 0.5766 | 0.5008 | 0.5766 |
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- | No log | 3.4118 | 58 | 0.7541 | 0.4405 | 0.7541 |
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- | No log | 3.5294 | 60 | 0.6666 | 0.4686 | 0.6666 |
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- | No log | 3.6471 | 62 | 0.5454 | 0.5289 | 0.5454 |
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- | No log | 3.7647 | 64 | 0.5373 | 0.5502 | 0.5373 |
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- | No log | 3.8824 | 66 | 0.5811 | 0.4814 | 0.5811 |
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- | No log | 4.0 | 68 | 0.8522 | 0.3958 | 0.8522 |
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- | No log | 4.1176 | 70 | 0.9611 | 0.3420 | 0.9611 |
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- | No log | 4.2353 | 72 | 0.7150 | 0.4366 | 0.7150 |
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- | No log | 4.3529 | 74 | 0.5129 | 0.5461 | 0.5129 |
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- | No log | 4.4706 | 76 | 0.5130 | 0.5731 | 0.5130 |
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- | No log | 4.5882 | 78 | 0.5549 | 0.5002 | 0.5549 |
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- | No log | 4.7059 | 80 | 0.6423 | 0.4682 | 0.6423 |
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- | No log | 4.8235 | 82 | 0.6433 | 0.4655 | 0.6433 |
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- | No log | 4.9412 | 84 | 0.6814 | 0.4383 | 0.6814 |
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- | No log | 5.0588 | 86 | 0.6506 | 0.4536 | 0.6506 |
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- | No log | 5.1765 | 88 | 0.6845 | 0.4340 | 0.6845 |
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- | No log | 5.2941 | 90 | 0.6105 | 0.4691 | 0.6105 |
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- | No log | 5.4118 | 92 | 0.5818 | 0.5096 | 0.5818 |
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- | No log | 5.5294 | 94 | 0.6505 | 0.4675 | 0.6505 |
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- | No log | 5.6471 | 96 | 0.8762 | 0.4031 | 0.8762 |
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- | No log | 5.7647 | 98 | 0.9354 | 0.3979 | 0.9354 |
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- | No log | 5.8824 | 100 | 0.7273 | 0.4370 | 0.7273 |
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- | No log | 6.0 | 102 | 0.5439 | 0.5370 | 0.5439 |
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- | No log | 6.1176 | 104 | 0.5275 | 0.5934 | 0.5275 |
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- | No log | 6.2353 | 106 | 0.5389 | 0.5407 | 0.5389 |
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- | No log | 6.3529 | 108 | 0.6632 | 0.4439 | 0.6632 |
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- | No log | 6.4706 | 110 | 0.7438 | 0.4262 | 0.7438 |
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- | No log | 6.5882 | 112 | 0.7194 | 0.4386 | 0.7194 |
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- | No log | 6.7059 | 114 | 0.6649 | 0.4611 | 0.6649 |
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- | No log | 6.8235 | 116 | 0.6469 | 0.4620 | 0.6469 |
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- | No log | 6.9412 | 118 | 0.6869 | 0.4426 | 0.6869 |
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- | No log | 7.0588 | 120 | 0.6784 | 0.4431 | 0.6784 |
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- | No log | 7.1765 | 122 | 0.6099 | 0.4604 | 0.6099 |
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- | No log | 7.2941 | 124 | 0.6103 | 0.4469 | 0.6103 |
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- | No log | 7.4118 | 126 | 0.6514 | 0.4384 | 0.6514 |
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- | No log | 7.5294 | 128 | 0.7174 | 0.4218 | 0.7174 |
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- | No log | 7.6471 | 130 | 0.7205 | 0.4218 | 0.7205 |
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- | No log | 7.7647 | 132 | 0.6510 | 0.4378 | 0.6510 |
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- | No log | 7.8824 | 134 | 0.5851 | 0.4688 | 0.5851 |
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- | No log | 8.0 | 136 | 0.5810 | 0.4909 | 0.5810 |
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- | No log | 8.1176 | 138 | 0.6226 | 0.4464 | 0.6226 |
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- | No log | 8.2353 | 140 | 0.7068 | 0.4404 | 0.7068 |
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- | No log | 8.3529 | 142 | 0.8169 | 0.4120 | 0.8169 |
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- | No log | 8.4706 | 144 | 0.8268 | 0.4106 | 0.8268 |
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- | No log | 8.5882 | 146 | 0.7821 | 0.4211 | 0.7821 |
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- | No log | 8.7059 | 148 | 0.7186 | 0.4252 | 0.7186 |
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- | No log | 8.8235 | 150 | 0.6896 | 0.4345 | 0.6896 |
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- | No log | 8.9412 | 152 | 0.6602 | 0.4409 | 0.6602 |
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- | No log | 9.0588 | 154 | 0.6525 | 0.4435 | 0.6525 |
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- | No log | 9.1765 | 156 | 0.6577 | 0.4435 | 0.6577 |
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- | No log | 9.2941 | 158 | 0.6779 | 0.4325 | 0.6779 |
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- | No log | 9.4118 | 160 | 0.7177 | 0.4166 | 0.7177 |
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- | No log | 9.5294 | 162 | 0.7502 | 0.4106 | 0.7502 |
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- | No log | 9.6471 | 164 | 0.7522 | 0.4057 | 0.7522 |
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- | No log | 9.7647 | 166 | 0.7503 | 0.4106 | 0.7503 |
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- | No log | 9.8824 | 168 | 0.7475 | 0.4150 | 0.7475 |
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- | No log | 10.0 | 170 | 0.7438 | 0.4143 | 0.7438 |
 
 
 
 
 
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  ### Framework versions
 
3
  tags:
4
  - generated_from_trainer
5
  model-index:
6
+ - name: arabert_cross_organization_task4_fold2
7
  results: []
8
  ---
9
 
10
  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
11
  should probably proofread and complete it, then remove this comment. -->
12
 
13
+ # arabert_cross_organization_task4_fold2
14
 
15
  This model is a fine-tuned version of [aubmindlab/bert-base-arabertv02](https://huggingface.co/aubmindlab/bert-base-arabertv02) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 1.7693
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+ - Qwk: -0.0357
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+ - Mse: 1.7659
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21
  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Qwk | Mse |
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  |:-------------:|:------:|:----:|:---------------:|:-------:|:------:|
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+ | No log | 0.1111 | 2 | 4.1886 | 0.0011 | 4.1850 |
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+ | No log | 0.2222 | 4 | 2.2640 | 0.0 | 2.2614 |
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+ | No log | 0.3333 | 6 | 1.3362 | 0.0183 | 1.3332 |
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+ | No log | 0.4444 | 8 | 0.9155 | 0.0 | 0.9122 |
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+ | No log | 0.5556 | 10 | 0.9188 | -0.0048 | 0.9152 |
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+ | No log | 0.6667 | 12 | 0.8902 | -0.0315 | 0.8872 |
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+ | No log | 0.7778 | 14 | 0.8950 | 0.0741 | 0.8923 |
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+ | No log | 0.8889 | 16 | 0.8770 | 0.0875 | 0.8744 |
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+ | No log | 1.0 | 18 | 0.8807 | 0.1030 | 0.8782 |
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+ | No log | 1.1111 | 20 | 0.8915 | -0.0099 | 0.8887 |
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+ | No log | 1.2222 | 22 | 0.9457 | 0.0424 | 0.9431 |
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+ | No log | 1.3333 | 24 | 1.0318 | 0.0182 | 1.0292 |
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+ | No log | 1.4444 | 26 | 1.1586 | 0.0 | 1.1562 |
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+ | No log | 1.5556 | 28 | 1.2936 | 0.0 | 1.2909 |
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+ | No log | 1.6667 | 30 | 1.4219 | 0.0 | 1.4193 |
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+ | No log | 1.7778 | 32 | 1.4842 | 0.0 | 1.4816 |
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+ | No log | 1.8889 | 34 | 1.4765 | 0.0 | 1.4737 |
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+ | No log | 2.0 | 36 | 1.4797 | 0.0 | 1.4769 |
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+ | No log | 2.1111 | 38 | 1.4454 | 0.0 | 1.4425 |
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+ | No log | 2.2222 | 40 | 1.5693 | 0.0 | 1.5665 |
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+ | No log | 2.3333 | 42 | 1.6763 | 0.0 | 1.6737 |
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+ | No log | 2.4444 | 44 | 1.6705 | 0.0 | 1.6677 |
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+ | No log | 2.5556 | 46 | 1.4309 | 0.0182 | 1.4278 |
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+ | No log | 2.6667 | 48 | 1.3201 | 0.0536 | 1.3169 |
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+ | No log | 2.7778 | 50 | 1.5069 | 0.0182 | 1.5037 |
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+ | No log | 2.8889 | 52 | 1.6390 | 0.0 | 1.6360 |
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+ | No log | 3.0 | 54 | 1.5712 | 0.0 | 1.5682 |
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+ | No log | 3.1111 | 56 | 1.4444 | 0.0182 | 1.4413 |
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+ | No log | 3.2222 | 58 | 1.3827 | 0.0182 | 1.3796 |
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+ | No log | 3.3333 | 60 | 1.5276 | 0.0 | 1.5245 |
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+ | No log | 3.4444 | 62 | 1.5680 | 0.0025 | 1.5650 |
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+ | No log | 3.5556 | 64 | 1.5963 | 0.0328 | 1.5931 |
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+ | No log | 3.6667 | 66 | 1.5027 | -0.0118 | 1.4994 |
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+ | No log | 3.7778 | 68 | 1.5906 | 0.0485 | 1.5873 |
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+ | No log | 3.8889 | 70 | 1.7316 | 0.0225 | 1.7284 |
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+ | No log | 4.0 | 72 | 1.6752 | 0.0160 | 1.6719 |
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+ | No log | 4.1111 | 74 | 1.4644 | 0.0136 | 1.4611 |
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+ | No log | 4.2222 | 76 | 1.2946 | 0.0498 | 1.2914 |
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+ | No log | 4.3333 | 78 | 1.3892 | 0.0571 | 1.3860 |
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+ | No log | 4.4444 | 80 | 1.6935 | 0.0183 | 1.6903 |
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+ | No log | 4.5556 | 82 | 1.8327 | 0.0026 | 1.8295 |
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+ | No log | 4.6667 | 84 | 1.7518 | 0.0272 | 1.7486 |
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+ | No log | 4.7778 | 86 | 1.5355 | 0.0437 | 1.5322 |
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+ | No log | 4.8889 | 88 | 1.4546 | 0.0750 | 1.4513 |
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+ | No log | 5.0 | 90 | 1.6165 | 0.0875 | 1.6132 |
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+ | No log | 5.1111 | 92 | 1.8925 | 0.0054 | 1.8891 |
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+ | No log | 5.2222 | 94 | 1.9400 | -0.0784 | 1.9366 |
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+ | No log | 5.3333 | 96 | 1.7667 | 0.0162 | 1.7634 |
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+ | No log | 5.4444 | 98 | 1.5714 | 0.0700 | 1.5681 |
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+ | No log | 5.5556 | 100 | 1.6393 | 0.0586 | 1.6360 |
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+ | No log | 5.6667 | 102 | 1.7094 | 0.0144 | 1.7060 |
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+ | No log | 5.7778 | 104 | 1.8384 | 0.0162 | 1.8349 |
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+ | No log | 5.8889 | 106 | 1.7972 | 0.0130 | 1.7937 |
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+ | No log | 6.0 | 108 | 1.7520 | 0.0113 | 1.7486 |
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+ | No log | 6.1111 | 110 | 1.6669 | 0.0264 | 1.6636 |
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+ | No log | 6.2222 | 112 | 1.6880 | 0.0301 | 1.6846 |
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+ | No log | 6.3333 | 114 | 1.7562 | 0.0096 | 1.7528 |
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+ | No log | 6.4444 | 116 | 1.7980 | 0.0228 | 1.7947 |
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+ | No log | 6.5556 | 118 | 1.8220 | -0.0199 | 1.8187 |
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+ | No log | 6.6667 | 120 | 1.7461 | 0.0746 | 1.7429 |
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+ | No log | 6.7778 | 122 | 1.5563 | 0.0272 | 1.5532 |
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+ | No log | 6.8889 | 124 | 1.4185 | 0.0655 | 1.4154 |
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+ | No log | 7.0 | 126 | 1.4690 | 0.0697 | 1.4658 |
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+ | No log | 7.1111 | 128 | 1.6412 | 0.0722 | 1.6381 |
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+ | No log | 7.2222 | 130 | 1.8101 | -0.0325 | 1.8069 |
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+ | No log | 7.3333 | 132 | 1.8161 | -0.0588 | 1.8129 |
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+ | No log | 7.4444 | 134 | 1.6991 | 0.0758 | 1.6959 |
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+ | No log | 7.5556 | 136 | 1.5693 | 0.0476 | 1.5661 |
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+ | No log | 7.6667 | 138 | 1.5215 | 0.0437 | 1.5183 |
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+ | No log | 7.7778 | 140 | 1.5990 | 0.0699 | 1.5957 |
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+ | No log | 7.8889 | 142 | 1.7382 | 0.0363 | 1.7348 |
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+ | No log | 8.0 | 144 | 1.8943 | -0.0587 | 1.8909 |
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+ | No log | 8.1111 | 146 | 1.9468 | -0.0675 | 1.9434 |
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+ | No log | 8.2222 | 148 | 1.9074 | -0.0587 | 1.9040 |
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+ | No log | 8.3333 | 150 | 1.8074 | -0.0208 | 1.8040 |
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+ | No log | 8.4444 | 152 | 1.7220 | 0.0241 | 1.7186 |
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+ | No log | 8.5556 | 154 | 1.6877 | 0.0352 | 1.6843 |
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+ | No log | 8.6667 | 156 | 1.7113 | 0.0222 | 1.7079 |
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+ | No log | 8.7778 | 158 | 1.7927 | -0.0208 | 1.7893 |
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+ | No log | 8.8889 | 160 | 1.8848 | -0.0477 | 1.8813 |
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+ | No log | 9.0 | 162 | 1.9430 | -0.0613 | 1.9396 |
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+ | No log | 9.1111 | 164 | 1.9388 | -0.0613 | 1.9354 |
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+ | No log | 9.2222 | 166 | 1.8894 | -0.0477 | 1.8860 |
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+ | No log | 9.3333 | 168 | 1.8314 | -0.0424 | 1.8279 |
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+ | No log | 9.4444 | 170 | 1.7625 | -0.0357 | 1.7591 |
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+ | No log | 9.5556 | 172 | 1.7335 | 0.0264 | 1.7302 |
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+ | No log | 9.6667 | 174 | 1.7407 | 0.0264 | 1.7373 |
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+ | No log | 9.7778 | 176 | 1.7576 | -0.0102 | 1.7543 |
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+ | No log | 9.8889 | 178 | 1.7644 | -0.0357 | 1.7610 |
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+ | No log | 10.0 | 180 | 1.7693 | -0.0357 | 1.7659 |
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  ### Framework versions