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ASAP_FineTuningBERT_AugV5_k1_task1_organization_fold3

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@@ -5,21 +5,21 @@ base_model: bert-base-uncased
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  tags:
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  - generated_from_trainer
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  model-index:
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- - name: ASAP_FineTuningBERT_AugV5_k1_task1_organization_fold2
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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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- # ASAP_FineTuningBERT_AugV5_k1_task1_organization_fold2
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  This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.5821
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- - Qwk: 0.5834
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- - Mse: 0.5823
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- - Rmse: 0.7631
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  ## Model description
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@@ -50,56 +50,56 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Qwk | Mse | Rmse |
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  |:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:------:|
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- | No log | 2.0 | 2 | 10.1102 | 0.0 | 10.1098 | 3.1796 |
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- | No log | 4.0 | 4 | 8.5153 | 0.0 | 8.5150 | 2.9181 |
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- | No log | 6.0 | 6 | 6.9130 | 0.0 | 6.9126 | 2.6292 |
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- | No log | 8.0 | 8 | 5.4748 | 0.0330 | 5.4746 | 2.3398 |
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- | 9.0382 | 10.0 | 10 | 4.4633 | 0.0039 | 4.4632 | 2.1126 |
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- | 9.0382 | 12.0 | 12 | 3.6149 | 0.0 | 3.6149 | 1.9013 |
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- | 9.0382 | 14.0 | 14 | 2.9219 | 0.0 | 2.9219 | 1.7093 |
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- | 9.0382 | 16.0 | 16 | 2.3959 | 0.0965 | 2.3959 | 1.5479 |
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- | 9.0382 | 18.0 | 18 | 1.9642 | 0.0539 | 1.9643 | 1.4015 |
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- | 4.332 | 20.0 | 20 | 1.6434 | 0.0334 | 1.6435 | 1.2820 |
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- | 4.332 | 22.0 | 22 | 1.4010 | 0.0334 | 1.4011 | 1.1837 |
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- | 4.332 | 24.0 | 24 | 1.1567 | 0.0307 | 1.1570 | 1.0756 |
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- | 4.332 | 26.0 | 26 | 1.0073 | 0.0437 | 1.0075 | 1.0038 |
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- | 4.332 | 28.0 | 28 | 0.8614 | 0.2354 | 0.8616 | 0.9282 |
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- | 2.2501 | 30.0 | 30 | 0.7297 | 0.4421 | 0.7300 | 0.8544 |
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- | 2.2501 | 32.0 | 32 | 0.6508 | 0.4824 | 0.6513 | 0.8070 |
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- | 2.2501 | 34.0 | 34 | 0.6363 | 0.4827 | 0.6366 | 0.7979 |
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- | 2.2501 | 36.0 | 36 | 0.5677 | 0.4278 | 0.5682 | 0.7538 |
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- | 2.2501 | 38.0 | 38 | 0.5781 | 0.4109 | 0.5787 | 0.7607 |
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- | 1.1902 | 40.0 | 40 | 0.5452 | 0.4652 | 0.5456 | 0.7386 |
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- | 1.1902 | 42.0 | 42 | 0.5406 | 0.4471 | 0.5411 | 0.7356 |
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- | 1.1902 | 44.0 | 44 | 0.5490 | 0.4776 | 0.5495 | 0.7413 |
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- | 1.1902 | 46.0 | 46 | 0.5443 | 0.5829 | 0.5448 | 0.7381 |
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- | 1.1902 | 48.0 | 48 | 0.5611 | 0.6050 | 0.5616 | 0.7494 |
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- | 0.6288 | 50.0 | 50 | 0.5506 | 0.5916 | 0.5510 | 0.7423 |
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- | 0.6288 | 52.0 | 52 | 0.5505 | 0.5904 | 0.5509 | 0.7422 |
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- | 0.6288 | 54.0 | 54 | 0.6214 | 0.5851 | 0.6219 | 0.7886 |
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- | 0.6288 | 56.0 | 56 | 0.5689 | 0.5814 | 0.5693 | 0.7545 |
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- | 0.6288 | 58.0 | 58 | 0.5470 | 0.5856 | 0.5473 | 0.7398 |
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- | 0.3387 | 60.0 | 60 | 0.6808 | 0.5546 | 0.6811 | 0.8253 |
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- | 0.3387 | 62.0 | 62 | 0.6377 | 0.5669 | 0.6380 | 0.7988 |
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- | 0.3387 | 64.0 | 64 | 0.5568 | 0.5775 | 0.5570 | 0.7463 |
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- | 0.3387 | 66.0 | 66 | 0.5775 | 0.5689 | 0.5777 | 0.7601 |
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- | 0.3387 | 68.0 | 68 | 0.6875 | 0.5494 | 0.6877 | 0.8293 |
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- | 0.1982 | 70.0 | 70 | 0.6655 | 0.5540 | 0.6657 | 0.8159 |
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- | 0.1982 | 72.0 | 72 | 0.5663 | 0.5536 | 0.5665 | 0.7527 |
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- | 0.1982 | 74.0 | 74 | 0.5523 | 0.5651 | 0.5524 | 0.7432 |
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- | 0.1982 | 76.0 | 76 | 0.6181 | 0.5537 | 0.6182 | 0.7863 |
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- | 0.1982 | 78.0 | 78 | 0.7374 | 0.5493 | 0.7376 | 0.8588 |
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- | 0.1267 | 80.0 | 80 | 0.6437 | 0.5732 | 0.6439 | 0.8024 |
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- | 0.1267 | 82.0 | 82 | 0.5785 | 0.5661 | 0.5787 | 0.7607 |
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- | 0.1267 | 84.0 | 84 | 0.5934 | 0.5702 | 0.5935 | 0.7704 |
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- | 0.1267 | 86.0 | 86 | 0.6109 | 0.5710 | 0.6111 | 0.7817 |
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- | 0.1267 | 88.0 | 88 | 0.6239 | 0.5727 | 0.6241 | 0.7900 |
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- | 0.0849 | 90.0 | 90 | 0.5956 | 0.5785 | 0.5958 | 0.7719 |
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- | 0.0849 | 92.0 | 92 | 0.5650 | 0.5675 | 0.5652 | 0.7518 |
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- | 0.0849 | 94.0 | 94 | 0.5627 | 0.5764 | 0.5628 | 0.7502 |
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- | 0.0849 | 96.0 | 96 | 0.5699 | 0.5769 | 0.5701 | 0.7550 |
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- | 0.0849 | 98.0 | 98 | 0.5772 | 0.5813 | 0.5773 | 0.7598 |
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- | 0.0726 | 100.0 | 100 | 0.5821 | 0.5834 | 0.5823 | 0.7631 |
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  ### Framework versions
 
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  tags:
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  - generated_from_trainer
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  model-index:
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+ - name: ASAP_FineTuningBERT_AugV5_k1_task1_organization_fold3
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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
13
  should probably proofread and complete it, then remove this comment. -->
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+ # ASAP_FineTuningBERT_AugV5_k1_task1_organization_fold3
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  This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.5472
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+ - Qwk: 0.6157
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+ - Mse: 0.5468
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+ - Rmse: 0.7395
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Qwk | Mse | Rmse |
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  |:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:------:|
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+ | No log | 2.0 | 2 | 10.1792 | 0.0 | 10.1785 | 3.1904 |
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+ | No log | 4.0 | 4 | 8.5089 | 0.0 | 8.5083 | 2.9169 |
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+ | No log | 6.0 | 6 | 6.9593 | 0.0 | 6.9588 | 2.6380 |
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+ | No log | 8.0 | 8 | 5.4856 | 0.0235 | 5.4854 | 2.3421 |
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+ | 8.9084 | 10.0 | 10 | 4.5301 | 0.0076 | 4.5301 | 2.1284 |
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+ | 8.9084 | 12.0 | 12 | 3.7061 | 0.0 | 3.7062 | 1.9252 |
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+ | 8.9084 | 14.0 | 14 | 3.0780 | 0.0 | 3.0783 | 1.7545 |
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+ | 8.9084 | 16.0 | 16 | 2.4917 | 0.0806 | 2.4921 | 1.5786 |
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+ | 8.9084 | 18.0 | 18 | 2.0632 | 0.0462 | 2.0637 | 1.4365 |
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+ | 4.248 | 20.0 | 20 | 1.7062 | 0.0365 | 1.7068 | 1.3064 |
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+ | 4.248 | 22.0 | 22 | 1.4205 | 0.0266 | 1.4211 | 1.1921 |
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+ | 4.248 | 24.0 | 24 | 1.2230 | 0.0365 | 1.2236 | 1.1062 |
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+ | 4.248 | 26.0 | 26 | 1.0188 | 0.0266 | 1.0194 | 1.0097 |
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+ | 4.248 | 28.0 | 28 | 0.9326 | 0.1345 | 0.9331 | 0.9660 |
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+ | 2.2317 | 30.0 | 30 | 0.7686 | 0.4194 | 0.7691 | 0.8770 |
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+ | 2.2317 | 32.0 | 32 | 0.6643 | 0.4239 | 0.6649 | 0.8154 |
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+ | 2.2317 | 34.0 | 34 | 0.6961 | 0.4841 | 0.6964 | 0.8345 |
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+ | 2.2317 | 36.0 | 36 | 0.5712 | 0.4966 | 0.5715 | 0.7560 |
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+ | 2.2317 | 38.0 | 38 | 0.5742 | 0.4828 | 0.5746 | 0.7580 |
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+ | 1.1982 | 40.0 | 40 | 0.6294 | 0.5328 | 0.6296 | 0.7935 |
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+ | 1.1982 | 42.0 | 42 | 0.5522 | 0.5493 | 0.5524 | 0.7432 |
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+ | 1.1982 | 44.0 | 44 | 0.5565 | 0.5326 | 0.5567 | 0.7461 |
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+ | 1.1982 | 46.0 | 46 | 0.5330 | 0.6138 | 0.5330 | 0.7300 |
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+ | 1.1982 | 48.0 | 48 | 0.5267 | 0.6243 | 0.5266 | 0.7257 |
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+ | 0.6088 | 50.0 | 50 | 0.5512 | 0.6109 | 0.5512 | 0.7424 |
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+ | 0.6088 | 52.0 | 52 | 0.5308 | 0.6299 | 0.5307 | 0.7285 |
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+ | 0.6088 | 54.0 | 54 | 0.5550 | 0.6454 | 0.5548 | 0.7449 |
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+ | 0.6088 | 56.0 | 56 | 0.5786 | 0.6130 | 0.5783 | 0.7605 |
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+ | 0.6088 | 58.0 | 58 | 0.5721 | 0.6516 | 0.5719 | 0.7562 |
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+ | 0.3243 | 60.0 | 60 | 0.5806 | 0.6334 | 0.5804 | 0.7618 |
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+ | 0.3243 | 62.0 | 62 | 0.5647 | 0.6108 | 0.5644 | 0.7513 |
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+ | 0.3243 | 64.0 | 64 | 0.5766 | 0.6371 | 0.5762 | 0.7591 |
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+ | 0.3243 | 66.0 | 66 | 0.6710 | 0.6038 | 0.6707 | 0.8190 |
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+ | 0.3243 | 68.0 | 68 | 0.6148 | 0.6469 | 0.6144 | 0.7838 |
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+ | 0.2165 | 70.0 | 70 | 0.6383 | 0.6439 | 0.6378 | 0.7986 |
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+ | 0.2165 | 72.0 | 72 | 0.6265 | 0.6445 | 0.6259 | 0.7912 |
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+ | 0.2165 | 74.0 | 74 | 0.5973 | 0.6427 | 0.5968 | 0.7725 |
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+ | 0.2165 | 76.0 | 76 | 0.5642 | 0.6337 | 0.5638 | 0.7509 |
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+ | 0.2165 | 78.0 | 78 | 0.6005 | 0.6137 | 0.6001 | 0.7747 |
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+ | 0.1667 | 80.0 | 80 | 0.5892 | 0.6100 | 0.5889 | 0.7674 |
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+ | 0.1667 | 82.0 | 82 | 0.5564 | 0.6097 | 0.5561 | 0.7457 |
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+ | 0.1667 | 84.0 | 84 | 0.5499 | 0.6275 | 0.5496 | 0.7413 |
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+ | 0.1667 | 86.0 | 86 | 0.5634 | 0.6148 | 0.5630 | 0.7503 |
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+ | 0.1667 | 88.0 | 88 | 0.5774 | 0.6205 | 0.5770 | 0.7596 |
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+ | 0.1285 | 90.0 | 90 | 0.5857 | 0.6113 | 0.5852 | 0.7650 |
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+ | 0.1285 | 92.0 | 92 | 0.5637 | 0.6233 | 0.5633 | 0.7505 |
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+ | 0.1285 | 94.0 | 94 | 0.5507 | 0.6195 | 0.5502 | 0.7418 |
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+ | 0.1285 | 96.0 | 96 | 0.5484 | 0.6197 | 0.5480 | 0.7403 |
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+ | 0.1285 | 98.0 | 98 | 0.5466 | 0.6224 | 0.5462 | 0.7390 |
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+ | 0.0925 | 100.0 | 100 | 0.5472 | 0.6157 | 0.5468 | 0.7395 |
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  ### Framework versions