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arabert_cross_development_task1_fold0

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bert
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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_task7_fold6
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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_task7_fold6
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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: 0.6600
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- - Qwk: 0.5581
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- - Mse: 0.6587
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  ## Model description
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@@ -45,88 +45,83 @@ 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 | 0.125 | 2 | 2.0463 | 0.0838 | 2.0448 |
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- | No log | 0.25 | 4 | 1.0746 | 0.1939 | 1.0725 |
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- | No log | 0.375 | 6 | 1.0643 | 0.3449 | 1.0639 |
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- | No log | 0.5 | 8 | 0.8689 | 0.5214 | 0.8684 |
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- | No log | 0.625 | 10 | 0.7524 | 0.3263 | 0.7518 |
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- | No log | 0.75 | 12 | 0.6423 | 0.3754 | 0.6420 |
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- | No log | 0.875 | 14 | 0.5644 | 0.5844 | 0.5643 |
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- | No log | 1.0 | 16 | 0.5224 | 0.6557 | 0.5223 |
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- | No log | 1.125 | 18 | 0.4855 | 0.6292 | 0.4850 |
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- | No log | 1.25 | 20 | 0.5779 | 0.5418 | 0.5767 |
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- | No log | 1.375 | 22 | 0.5208 | 0.6043 | 0.5197 |
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- | No log | 1.5 | 24 | 0.5175 | 0.7174 | 0.5174 |
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- | No log | 1.625 | 26 | 0.4998 | 0.7107 | 0.4998 |
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- | No log | 1.75 | 28 | 0.4818 | 0.6457 | 0.4809 |
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- | No log | 1.875 | 30 | 0.4990 | 0.6364 | 0.4979 |
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- | No log | 2.0 | 32 | 0.5085 | 0.6403 | 0.5073 |
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- | No log | 2.125 | 34 | 0.4978 | 0.6611 | 0.4969 |
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- | No log | 2.25 | 36 | 0.4811 | 0.6848 | 0.4805 |
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- | No log | 2.375 | 38 | 0.4675 | 0.6672 | 0.4669 |
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- | No log | 2.5 | 40 | 0.4889 | 0.6232 | 0.4881 |
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- | No log | 2.625 | 42 | 0.5071 | 0.6102 | 0.5062 |
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- | No log | 2.75 | 44 | 0.5162 | 0.6263 | 0.5151 |
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- | No log | 2.875 | 46 | 0.5184 | 0.6317 | 0.5172 |
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- | No log | 3.0 | 48 | 0.5229 | 0.6543 | 0.5219 |
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- | No log | 3.125 | 50 | 0.5389 | 0.6233 | 0.5377 |
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- | No log | 3.25 | 52 | 0.5879 | 0.5675 | 0.5861 |
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- | No log | 3.375 | 54 | 0.6183 | 0.5488 | 0.6164 |
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- | No log | 3.5 | 56 | 0.5578 | 0.5898 | 0.5563 |
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- | No log | 3.625 | 58 | 0.5612 | 0.6909 | 0.5607 |
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- | No log | 3.75 | 60 | 0.5964 | 0.7100 | 0.5962 |
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- | No log | 3.875 | 62 | 0.5615 | 0.6815 | 0.5609 |
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- | No log | 4.0 | 64 | 0.5730 | 0.5963 | 0.5716 |
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- | No log | 4.125 | 66 | 0.6867 | 0.5243 | 0.6849 |
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- | No log | 4.25 | 68 | 0.6700 | 0.5276 | 0.6682 |
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- | No log | 4.375 | 70 | 0.5889 | 0.5659 | 0.5873 |
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- | No log | 4.5 | 72 | 0.5446 | 0.6149 | 0.5434 |
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- | No log | 4.625 | 74 | 0.5556 | 0.6355 | 0.5547 |
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- | No log | 4.75 | 76 | 0.5886 | 0.6034 | 0.5871 |
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- | No log | 4.875 | 78 | 0.6730 | 0.5568 | 0.6709 |
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- | No log | 5.0 | 80 | 0.6892 | 0.5344 | 0.6871 |
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- | No log | 5.125 | 82 | 0.6046 | 0.5665 | 0.6029 |
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- | No log | 5.25 | 84 | 0.5605 | 0.6134 | 0.5591 |
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- | No log | 5.375 | 86 | 0.5415 | 0.6417 | 0.5404 |
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- | No log | 5.5 | 88 | 0.5515 | 0.6247 | 0.5504 |
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- | No log | 5.625 | 90 | 0.5964 | 0.5762 | 0.5948 |
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- | No log | 5.75 | 92 | 0.6466 | 0.5489 | 0.6449 |
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- | No log | 5.875 | 94 | 0.6325 | 0.5648 | 0.6310 |
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- | No log | 6.0 | 96 | 0.6036 | 0.6097 | 0.6022 |
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- | No log | 6.125 | 98 | 0.5955 | 0.6483 | 0.5944 |
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- | No log | 6.25 | 100 | 0.6017 | 0.6168 | 0.6005 |
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- | No log | 6.375 | 102 | 0.6349 | 0.5846 | 0.6335 |
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- | No log | 6.5 | 104 | 0.6941 | 0.5277 | 0.6925 |
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- | No log | 6.625 | 106 | 0.6740 | 0.5262 | 0.6724 |
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- | No log | 6.75 | 108 | 0.6043 | 0.5829 | 0.6030 |
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- | No log | 6.875 | 110 | 0.5813 | 0.6039 | 0.5802 |
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- | No log | 7.0 | 112 | 0.5847 | 0.6056 | 0.5836 |
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- | No log | 7.125 | 114 | 0.6031 | 0.5987 | 0.6019 |
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- | No log | 7.25 | 116 | 0.6490 | 0.5645 | 0.6474 |
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- | No log | 7.375 | 118 | 0.6772 | 0.5326 | 0.6756 |
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- | No log | 7.5 | 120 | 0.6849 | 0.5311 | 0.6833 |
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- | No log | 7.625 | 122 | 0.6620 | 0.5393 | 0.6606 |
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- | No log | 7.75 | 124 | 0.6230 | 0.5696 | 0.6217 |
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- | No log | 7.875 | 126 | 0.5912 | 0.5983 | 0.5901 |
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- | No log | 8.0 | 128 | 0.5924 | 0.5983 | 0.5913 |
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- | No log | 8.125 | 130 | 0.6124 | 0.5864 | 0.6112 |
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- | No log | 8.25 | 132 | 0.6364 | 0.5615 | 0.6351 |
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- | No log | 8.375 | 134 | 0.6650 | 0.5476 | 0.6635 |
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- | No log | 8.5 | 136 | 0.6693 | 0.5397 | 0.6678 |
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- | No log | 8.625 | 138 | 0.6639 | 0.5516 | 0.6624 |
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- | No log | 8.75 | 140 | 0.6658 | 0.5467 | 0.6643 |
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- | No log | 8.875 | 142 | 0.6772 | 0.5437 | 0.6757 |
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- | No log | 9.0 | 144 | 0.6778 | 0.5489 | 0.6763 |
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- | No log | 9.125 | 146 | 0.6641 | 0.5504 | 0.6627 |
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- | No log | 9.25 | 148 | 0.6614 | 0.5557 | 0.6600 |
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- | No log | 9.375 | 150 | 0.6564 | 0.5609 | 0.6551 |
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- | No log | 9.5 | 152 | 0.6530 | 0.5618 | 0.6517 |
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- | No log | 9.625 | 154 | 0.6533 | 0.5618 | 0.6520 |
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- | No log | 9.75 | 156 | 0.6546 | 0.5581 | 0.6533 |
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- | No log | 9.875 | 158 | 0.6579 | 0.5581 | 0.6566 |
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- | No log | 10.0 | 160 | 0.6600 | 0.5581 | 0.6587 |
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  ### Framework versions
 
3
  tags:
4
  - generated_from_trainer
5
  model-index:
6
+ - name: arabert_cross_development_task1_fold0
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_development_task1_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: 0.8306
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+ - Qwk: 0.2565
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+ - Mse: 0.8306
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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 | 0.1333 | 2 | 4.0034 | -0.0039 | 4.0034 |
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+ | No log | 0.2667 | 4 | 1.7572 | 0.0385 | 1.7572 |
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+ | No log | 0.4 | 6 | 0.8795 | 0.1253 | 0.8795 |
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+ | No log | 0.5333 | 8 | 1.0722 | 0.1468 | 1.0722 |
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+ | No log | 0.6667 | 10 | 1.9981 | 0.0739 | 1.9981 |
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+ | No log | 0.8 | 12 | 1.4228 | 0.1298 | 1.4228 |
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+ | No log | 0.9333 | 14 | 0.7120 | 0.1720 | 0.7120 |
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+ | No log | 1.0667 | 16 | 0.5182 | 0.2951 | 0.5182 |
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+ | No log | 1.2 | 18 | 0.6133 | 0.2736 | 0.6133 |
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+ | No log | 1.3333 | 20 | 1.1336 | 0.1776 | 1.1336 |
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+ | No log | 1.4667 | 22 | 1.2656 | 0.1714 | 1.2656 |
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+ | No log | 1.6 | 24 | 0.8675 | 0.2380 | 0.8675 |
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+ | No log | 1.7333 | 26 | 0.5730 | 0.3050 | 0.5730 |
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+ | No log | 1.8667 | 28 | 0.5924 | 0.2784 | 0.5924 |
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+ | No log | 2.0 | 30 | 0.6861 | 0.2120 | 0.6861 |
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+ | No log | 2.1333 | 32 | 0.8867 | 0.2029 | 0.8867 |
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+ | No log | 2.2667 | 34 | 0.9172 | 0.2121 | 0.9172 |
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+ | No log | 2.4 | 36 | 0.7721 | 0.2159 | 0.7721 |
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+ | No log | 2.5333 | 38 | 0.8001 | 0.2277 | 0.8001 |
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+ | No log | 2.6667 | 40 | 0.8684 | 0.2498 | 0.8684 |
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+ | No log | 2.8 | 42 | 0.9570 | 0.2264 | 0.9570 |
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+ | No log | 2.9333 | 44 | 0.8803 | 0.2439 | 0.8803 |
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+ | No log | 3.0667 | 46 | 0.7435 | 0.2799 | 0.7435 |
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+ | No log | 3.2 | 48 | 0.6805 | 0.3082 | 0.6805 |
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+ | No log | 3.3333 | 50 | 0.8424 | 0.2730 | 0.8424 |
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+ | No log | 3.4667 | 52 | 0.8402 | 0.2670 | 0.8402 |
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+ | No log | 3.6 | 54 | 0.8115 | 0.2861 | 0.8115 |
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+ | No log | 3.7333 | 56 | 0.8179 | 0.2776 | 0.8179 |
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+ | No log | 3.8667 | 58 | 0.7692 | 0.2822 | 0.7692 |
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+ | No log | 4.0 | 60 | 0.6605 | 0.2944 | 0.6605 |
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+ | No log | 4.1333 | 62 | 0.6724 | 0.3033 | 0.6724 |
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+ | No log | 4.2667 | 64 | 0.7918 | 0.2700 | 0.7918 |
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+ | No log | 4.4 | 66 | 0.9373 | 0.2649 | 0.9373 |
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+ | No log | 4.5333 | 68 | 0.8734 | 0.2482 | 0.8734 |
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+ | No log | 4.6667 | 70 | 0.6994 | 0.2866 | 0.6994 |
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+ | No log | 4.8 | 72 | 0.5761 | 0.3307 | 0.5761 |
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+ | No log | 4.9333 | 74 | 0.6497 | 0.2879 | 0.6497 |
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+ | No log | 5.0667 | 76 | 0.7333 | 0.2628 | 0.7333 |
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+ | No log | 5.2 | 78 | 1.0341 | 0.2345 | 1.0341 |
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+ | No log | 5.3333 | 80 | 1.1378 | 0.2214 | 1.1378 |
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+ | No log | 5.4667 | 82 | 0.9255 | 0.2527 | 0.9255 |
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+ | No log | 5.6 | 84 | 0.6589 | 0.3108 | 0.6589 |
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+ | No log | 5.7333 | 86 | 0.5709 | 0.3576 | 0.5709 |
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+ | No log | 5.8667 | 88 | 0.6392 | 0.2982 | 0.6392 |
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+ | No log | 6.0 | 90 | 0.7919 | 0.2436 | 0.7919 |
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+ | No log | 6.1333 | 92 | 0.7855 | 0.2412 | 0.7855 |
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+ | No log | 6.2667 | 94 | 0.6800 | 0.2919 | 0.6800 |
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+ | No log | 6.4 | 96 | 0.6850 | 0.2998 | 0.6850 |
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+ | No log | 6.5333 | 98 | 0.8473 | 0.2545 | 0.8473 |
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+ | No log | 6.6667 | 100 | 0.9780 | 0.2417 | 0.9780 |
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+ | No log | 6.8 | 102 | 0.9663 | 0.2331 | 0.9663 |
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+ | No log | 6.9333 | 104 | 0.8213 | 0.2337 | 0.8213 |
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+ | No log | 7.0667 | 106 | 0.6942 | 0.2789 | 0.6942 |
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+ | No log | 7.2 | 108 | 0.7119 | 0.2738 | 0.7119 |
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+ | No log | 7.3333 | 110 | 0.8067 | 0.2517 | 0.8067 |
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+ | No log | 7.4667 | 112 | 0.8998 | 0.2447 | 0.8998 |
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+ | No log | 7.6 | 114 | 0.9907 | 0.2199 | 0.9907 |
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+ | No log | 7.7333 | 116 | 0.9290 | 0.2364 | 0.9290 |
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+ | No log | 7.8667 | 118 | 0.7925 | 0.2551 | 0.7925 |
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+ | No log | 8.0 | 120 | 0.7137 | 0.2738 | 0.7137 |
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+ | No log | 8.1333 | 122 | 0.7202 | 0.2753 | 0.7202 |
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+ | No log | 8.2667 | 124 | 0.7738 | 0.2663 | 0.7738 |
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+ | No log | 8.4 | 126 | 0.8078 | 0.2539 | 0.8078 |
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+ | No log | 8.5333 | 128 | 0.8794 | 0.2516 | 0.8794 |
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+ | No log | 8.6667 | 130 | 0.9809 | 0.2362 | 0.9809 |
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+ | No log | 8.8 | 132 | 1.0066 | 0.2362 | 1.0066 |
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+ | No log | 8.9333 | 134 | 0.9524 | 0.2397 | 0.9524 |
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+ | No log | 9.0667 | 136 | 0.8849 | 0.2464 | 0.8849 |
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+ | No log | 9.2 | 138 | 0.8285 | 0.2565 | 0.8285 |
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+ | No log | 9.3333 | 140 | 0.7806 | 0.2545 | 0.7806 |
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+ | No log | 9.4667 | 142 | 0.7707 | 0.2569 | 0.7707 |
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+ | No log | 9.6 | 144 | 0.7836 | 0.2545 | 0.7836 |
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+ | No log | 9.7333 | 146 | 0.8063 | 0.2550 | 0.8063 |
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+ | No log | 9.8667 | 148 | 0.8258 | 0.2565 | 0.8258 |
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+ | No log | 10.0 | 150 | 0.8306 | 0.2565 | 0.8306 |
 
 
 
 
 
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  ### Framework versions