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arabert_cross_organization_task4_fold1

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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_fold0
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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_fold0
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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: 0.7387
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- - Qwk: 0.5925
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- - Mse: 0.7387
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  ## Model description
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@@ -45,93 +45,93 @@ The following hyperparameters were used during training:
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  ### Training results
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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 | 3.7003 | 0.0594 | 3.6971 |
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- | No log | 0.2353 | 4 | 2.4103 | 0.0127 | 2.4085 |
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- | No log | 0.3529 | 6 | 1.7582 | 0.2177 | 1.7571 |
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- | No log | 0.4706 | 8 | 1.5666 | 0.3222 | 1.5658 |
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- | No log | 0.5882 | 10 | 0.9860 | 0.4576 | 0.9866 |
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- | No log | 0.7059 | 12 | 0.9585 | 0.5399 | 0.9591 |
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- | No log | 0.8235 | 14 | 1.3953 | 0.4078 | 1.3949 |
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- | No log | 0.9412 | 16 | 1.6278 | 0.3501 | 1.6269 |
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- | No log | 1.0588 | 18 | 1.2485 | 0.4062 | 1.2480 |
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- | No log | 1.1765 | 20 | 0.9325 | 0.4653 | 0.9323 |
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- | No log | 1.2941 | 22 | 0.8750 | 0.5046 | 0.8747 |
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- | No log | 1.4118 | 24 | 0.9684 | 0.4851 | 0.9679 |
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- | No log | 1.5294 | 26 | 1.3655 | 0.3843 | 1.3644 |
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- | No log | 1.6471 | 28 | 1.0699 | 0.4636 | 1.0693 |
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- | No log | 1.7647 | 30 | 0.7323 | 0.6264 | 0.7322 |
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- | No log | 1.8824 | 32 | 0.7409 | 0.6340 | 0.7408 |
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- | No log | 2.0 | 34 | 0.7342 | 0.6187 | 0.7341 |
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- | No log | 2.1176 | 36 | 0.7935 | 0.5765 | 0.7932 |
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- | No log | 2.2353 | 38 | 1.0980 | 0.4535 | 1.0972 |
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- | No log | 2.3529 | 40 | 1.0511 | 0.4714 | 1.0504 |
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- | No log | 2.4706 | 42 | 0.8556 | 0.5268 | 0.8552 |
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- | No log | 2.5882 | 44 | 0.7684 | 0.5983 | 0.7681 |
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- | No log | 2.7059 | 46 | 0.8207 | 0.5721 | 0.8206 |
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- | No log | 2.8235 | 48 | 0.9052 | 0.5593 | 0.9050 |
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- | No log | 2.9412 | 50 | 0.8417 | 0.5743 | 0.8416 |
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- | No log | 3.0588 | 52 | 0.7671 | 0.6038 | 0.7671 |
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- | No log | 3.1765 | 54 | 0.7859 | 0.5949 | 0.7859 |
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- | No log | 3.2941 | 56 | 0.8844 | 0.5560 | 0.8842 |
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- | No log | 3.4118 | 58 | 0.9141 | 0.5516 | 0.9137 |
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- | No log | 3.5294 | 60 | 0.7828 | 0.5943 | 0.7825 |
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- | No log | 3.6471 | 62 | 0.7194 | 0.6082 | 0.7191 |
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- | No log | 3.7647 | 64 | 0.7235 | 0.6070 | 0.7233 |
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- | No log | 3.8824 | 66 | 0.7606 | 0.5926 | 0.7604 |
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- | No log | 4.0 | 68 | 0.9394 | 0.5299 | 0.9388 |
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- | No log | 4.1176 | 70 | 0.9642 | 0.5092 | 0.9636 |
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- | No log | 4.2353 | 72 | 0.7479 | 0.5973 | 0.7477 |
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- | No log | 4.3529 | 74 | 0.6642 | 0.6133 | 0.6642 |
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- | No log | 4.4706 | 76 | 0.6706 | 0.6129 | 0.6705 |
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- | No log | 4.5882 | 78 | 0.7184 | 0.6006 | 0.7183 |
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- | No log | 4.7059 | 80 | 0.7525 | 0.5921 | 0.7523 |
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- | No log | 4.8235 | 82 | 0.7429 | 0.5934 | 0.7428 |
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- | No log | 4.9412 | 84 | 0.7555 | 0.5857 | 0.7554 |
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- | No log | 5.0588 | 86 | 0.7166 | 0.5978 | 0.7165 |
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- | No log | 5.1765 | 88 | 0.7034 | 0.5949 | 0.7033 |
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- | No log | 5.2941 | 90 | 0.7179 | 0.5869 | 0.7178 |
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- | No log | 5.4118 | 92 | 0.8419 | 0.5574 | 0.8416 |
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- | No log | 5.5294 | 94 | 0.9040 | 0.5229 | 0.9037 |
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- | No log | 5.6471 | 96 | 0.8841 | 0.5357 | 0.8839 |
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- | No log | 5.7647 | 98 | 0.7383 | 0.5893 | 0.7383 |
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- | No log | 5.8824 | 100 | 0.6787 | 0.6146 | 0.6789 |
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- | No log | 6.0 | 102 | 0.6933 | 0.6105 | 0.6933 |
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- | No log | 6.1176 | 104 | 0.7751 | 0.5812 | 0.7749 |
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- | No log | 6.2353 | 106 | 0.7938 | 0.5700 | 0.7936 |
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- | No log | 6.3529 | 108 | 0.7205 | 0.6067 | 0.7204 |
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- | No log | 6.4706 | 110 | 0.6695 | 0.6121 | 0.6695 |
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- | No log | 6.5882 | 112 | 0.6759 | 0.6171 | 0.6758 |
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- | No log | 6.7059 | 114 | 0.6919 | 0.6099 | 0.6918 |
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- | No log | 6.8235 | 116 | 0.7467 | 0.5990 | 0.7465 |
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- | No log | 6.9412 | 118 | 0.7453 | 0.5978 | 0.7452 |
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- | No log | 7.0588 | 120 | 0.7515 | 0.5967 | 0.7514 |
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- | No log | 7.1765 | 122 | 0.7221 | 0.6021 | 0.7221 |
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- | No log | 7.2941 | 124 | 0.7307 | 0.6043 | 0.7307 |
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- | No log | 7.4118 | 126 | 0.7413 | 0.6043 | 0.7414 |
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- | No log | 7.5294 | 128 | 0.7247 | 0.6004 | 0.7249 |
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- | No log | 7.6471 | 130 | 0.7088 | 0.6058 | 0.7091 |
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- | No log | 7.7647 | 132 | 0.7232 | 0.6037 | 0.7235 |
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- | No log | 7.8824 | 134 | 0.7747 | 0.5935 | 0.7748 |
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- | No log | 8.0 | 136 | 0.8677 | 0.5568 | 0.8676 |
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- | No log | 8.1176 | 138 | 0.8769 | 0.5521 | 0.8768 |
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- | No log | 8.2353 | 140 | 0.8117 | 0.5845 | 0.8116 |
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- | No log | 8.3529 | 142 | 0.7379 | 0.5954 | 0.7379 |
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- | No log | 8.4706 | 144 | 0.7203 | 0.6024 | 0.7203 |
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- | No log | 8.5882 | 146 | 0.7255 | 0.6036 | 0.7255 |
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- | No log | 8.7059 | 148 | 0.7177 | 0.6024 | 0.7177 |
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- | No log | 8.8235 | 150 | 0.7099 | 0.6036 | 0.7099 |
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- | No log | 8.9412 | 152 | 0.7149 | 0.6036 | 0.7150 |
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- | No log | 9.0588 | 154 | 0.7323 | 0.5976 | 0.7323 |
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- | No log | 9.1765 | 156 | 0.7453 | 0.5919 | 0.7453 |
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- | No log | 9.2941 | 158 | 0.7533 | 0.5901 | 0.7533 |
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- | No log | 9.4118 | 160 | 0.7538 | 0.5902 | 0.7538 |
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- | No log | 9.5294 | 162 | 0.7490 | 0.5903 | 0.7490 |
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- | No log | 9.6471 | 164 | 0.7411 | 0.5952 | 0.7411 |
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- | No log | 9.7647 | 166 | 0.7407 | 0.5952 | 0.7407 |
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- | No log | 9.8824 | 168 | 0.7383 | 0.5925 | 0.7383 |
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- | No log | 10.0 | 170 | 0.7387 | 0.5925 | 0.7387 |
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  ### Framework versions
 
3
  tags:
4
  - generated_from_trainer
5
  model-index:
6
+ - name: arabert_cross_organization_task4_fold1
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_fold1
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: 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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  ### Training results
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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