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arabert_cross_organization_task1_fold2

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  1. README.md +90 -42
  2. model.safetensors +1 -1
  3. training_args.bin +1 -1
README.md CHANGED
@@ -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_task1_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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- # arabert_cross_organization_task1_fold2
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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: 1.1151
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- - Qwk: 0.0397
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- - Mse: 1.1151
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  ## Model description
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@@ -36,49 +36,97 @@ More information needed
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  The following hyperparameters were used during training:
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  - learning_rate: 2e-05
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- - train_batch_size: 16
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- - eval_batch_size: 16
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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: 1
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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 | 0.0308 | 2 | 8.1063 | 0.0 | 8.1063 |
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- | No log | 0.0615 | 4 | 4.3611 | 0.0014 | 4.3611 |
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- | No log | 0.0923 | 6 | 2.2521 | 0.0584 | 2.2521 |
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- | No log | 0.1231 | 8 | 1.4384 | 0.0131 | 1.4384 |
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- | No log | 0.1538 | 10 | 1.0665 | 0.1602 | 1.0665 |
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- | No log | 0.1846 | 12 | 1.0608 | 0.0513 | 1.0608 |
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- | No log | 0.2154 | 14 | 1.0636 | 0.0036 | 1.0636 |
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- | No log | 0.2462 | 16 | 1.0686 | 0.0036 | 1.0686 |
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- | No log | 0.2769 | 18 | 1.0668 | 0.0036 | 1.0668 |
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- | No log | 0.3077 | 20 | 1.0565 | 0.0036 | 1.0565 |
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- | No log | 0.3385 | 22 | 1.0769 | 0.0289 | 1.0769 |
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- | No log | 0.3692 | 24 | 1.0972 | 0.0487 | 1.0972 |
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- | No log | 0.4 | 26 | 1.1159 | 0.0549 | 1.1159 |
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- | No log | 0.4308 | 28 | 1.1270 | 0.0151 | 1.1270 |
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- | No log | 0.4615 | 30 | 1.1101 | 0.0506 | 1.1101 |
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- | No log | 0.4923 | 32 | 1.0734 | 0.0639 | 1.0734 |
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- | No log | 0.5231 | 34 | 1.0767 | 0.0 | 1.0767 |
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- | No log | 0.5538 | 36 | 1.0893 | -0.0185 | 1.0893 |
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- | No log | 0.5846 | 38 | 1.0994 | -0.0366 | 1.0994 |
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- | No log | 0.6154 | 40 | 1.1021 | -0.0710 | 1.1021 |
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- | No log | 0.6462 | 42 | 1.1002 | -0.0366 | 1.1002 |
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- | No log | 0.6769 | 44 | 1.1002 | -0.0366 | 1.1002 |
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- | No log | 0.7077 | 46 | 1.0992 | -0.0366 | 1.0992 |
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- | No log | 0.7385 | 48 | 1.0933 | -0.0366 | 1.0933 |
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- | No log | 0.7692 | 50 | 1.0949 | 0.0170 | 1.0949 |
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- | No log | 0.8 | 52 | 1.1043 | 0.0338 | 1.1043 |
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- | No log | 0.8308 | 54 | 1.1170 | 0.0169 | 1.1170 |
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- | No log | 0.8615 | 56 | 1.1228 | 0.0651 | 1.1228 |
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- | No log | 0.8923 | 58 | 1.1212 | 0.0474 | 1.1212 |
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- | No log | 0.9231 | 60 | 1.1220 | 0.0474 | 1.1220 |
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- | No log | 0.9538 | 62 | 1.1176 | 0.0397 | 1.1176 |
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- | No log | 0.9846 | 64 | 1.1151 | 0.0397 | 1.1151 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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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: arabert_cross_organization_task1_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_task1_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: 0.9947
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+ - Qwk: 0.0679
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+ - Mse: 0.9916
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  ## Model description
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  The following hyperparameters were used during training:
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  - learning_rate: 2e-05
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+ - train_batch_size: 64
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+ - eval_batch_size: 64
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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: 10
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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 | 5.2049 | -0.0008 | 5.2020 |
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+ | No log | 0.25 | 4 | 1.9284 | -0.0122 | 1.9256 |
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+ | No log | 0.375 | 6 | 1.0209 | 0.0513 | 1.0167 |
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+ | No log | 0.5 | 8 | 0.8405 | 0.0824 | 0.8373 |
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+ | No log | 0.625 | 10 | 0.8656 | 0.1060 | 0.8628 |
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+ | No log | 0.75 | 12 | 0.8332 | 0.1240 | 0.8306 |
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+ | No log | 0.875 | 14 | 0.8775 | 0.0730 | 0.8754 |
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+ | No log | 1.0 | 16 | 0.9183 | 0.0104 | 0.9162 |
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+ | No log | 1.125 | 18 | 0.9057 | 0.0508 | 0.9032 |
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+ | No log | 1.25 | 20 | 0.8886 | 0.1273 | 0.8859 |
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+ | No log | 1.375 | 22 | 0.9957 | 0.0849 | 0.9930 |
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+ | No log | 1.5 | 24 | 1.0595 | 0.1181 | 1.0564 |
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+ | No log | 1.625 | 26 | 1.2289 | 0.0182 | 1.2258 |
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+ | No log | 1.75 | 28 | 1.2976 | 0.0182 | 1.2948 |
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+ | No log | 1.875 | 30 | 0.9648 | 0.1402 | 0.9617 |
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+ | No log | 2.0 | 32 | 0.9714 | 0.1016 | 0.9684 |
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+ | No log | 2.125 | 34 | 0.9511 | 0.0710 | 0.9483 |
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+ | No log | 2.25 | 36 | 0.8591 | 0.1425 | 0.8564 |
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+ | No log | 2.375 | 38 | 0.8696 | 0.1182 | 0.8667 |
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+ | No log | 2.5 | 40 | 1.0662 | 0.0360 | 1.0635 |
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+ | No log | 2.625 | 42 | 1.1724 | 0.0360 | 1.1696 |
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+ | No log | 2.75 | 44 | 1.3100 | 0.0182 | 1.3071 |
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+ | No log | 2.875 | 46 | 1.3304 | 0.0182 | 1.3275 |
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+ | No log | 3.0 | 48 | 1.0676 | 0.0424 | 1.0645 |
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+ | No log | 3.125 | 50 | 0.9732 | 0.0668 | 0.9701 |
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+ | No log | 3.25 | 52 | 1.1173 | 0.0279 | 1.1143 |
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+ | No log | 3.375 | 54 | 1.2420 | 0.0182 | 1.2393 |
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+ | No log | 3.5 | 56 | 1.1410 | 0.0155 | 1.1382 |
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+ | No log | 3.625 | 58 | 0.9316 | 0.0268 | 0.9285 |
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+ | No log | 3.75 | 60 | 0.8907 | 0.1122 | 0.8876 |
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+ | No log | 3.875 | 62 | 1.0183 | 0.0253 | 1.0153 |
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+ | No log | 4.0 | 64 | 1.1271 | 0.0279 | 1.1242 |
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+ | No log | 4.125 | 66 | 1.1742 | 0.0300 | 1.1712 |
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+ | No log | 4.25 | 68 | 1.2066 | 0.0682 | 1.2034 |
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+ | No log | 4.375 | 70 | 1.2604 | 0.0377 | 1.2572 |
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+ | No log | 4.5 | 72 | 1.1679 | 0.0830 | 1.1646 |
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+ | No log | 4.625 | 74 | 1.1770 | 0.0966 | 1.1739 |
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+ | No log | 4.75 | 76 | 1.1163 | 0.0966 | 1.1131 |
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+ | No log | 4.875 | 78 | 0.9754 | 0.0695 | 0.9721 |
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+ | No log | 5.0 | 80 | 0.9489 | 0.0767 | 0.9456 |
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+ | No log | 5.125 | 82 | 0.9900 | 0.0994 | 0.9868 |
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+ | No log | 5.25 | 84 | 0.8622 | 0.0654 | 0.8588 |
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+ | No log | 5.375 | 86 | 0.8621 | 0.1028 | 0.8586 |
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+ | No log | 5.5 | 88 | 1.0043 | 0.0807 | 1.0011 |
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+ | No log | 5.625 | 90 | 1.0565 | 0.0448 | 1.0533 |
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+ | No log | 5.75 | 92 | 0.9899 | 0.0848 | 0.9866 |
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+ | No log | 5.875 | 94 | 1.1141 | 0.0466 | 1.1111 |
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+ | No log | 6.0 | 96 | 1.3040 | 0.0906 | 1.3012 |
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+ | No log | 6.125 | 98 | 1.2856 | 0.1112 | 1.2829 |
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+ | No log | 6.25 | 100 | 1.3671 | 0.0962 | 1.3644 |
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+ | No log | 6.375 | 102 | 1.2601 | 0.1091 | 1.2574 |
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+ | No log | 6.5 | 104 | 1.2039 | 0.1595 | 1.2011 |
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+ | No log | 6.625 | 106 | 1.1272 | 0.0913 | 1.1244 |
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+ | No log | 6.75 | 108 | 1.0754 | 0.0958 | 1.0725 |
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+ | No log | 6.875 | 110 | 1.0818 | 0.0777 | 1.0790 |
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+ | No log | 7.0 | 112 | 1.0175 | 0.0670 | 1.0146 |
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+ | No log | 7.125 | 114 | 0.9552 | 0.0569 | 0.9521 |
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+ | No log | 7.25 | 116 | 0.8938 | 0.1278 | 0.8906 |
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+ | No log | 7.375 | 118 | 0.9486 | 0.0697 | 0.9455 |
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+ | No log | 7.5 | 120 | 0.9351 | 0.0773 | 0.9319 |
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+ | No log | 7.625 | 122 | 0.8928 | 0.0870 | 0.8895 |
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+ | No log | 7.75 | 124 | 0.8558 | 0.1373 | 0.8524 |
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+ | No log | 7.875 | 126 | 0.8561 | 0.1606 | 0.8527 |
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+ | No log | 8.0 | 128 | 0.9205 | 0.0389 | 0.9174 |
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+ | No log | 8.125 | 130 | 1.0514 | 0.0941 | 1.0484 |
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+ | No log | 8.25 | 132 | 1.0795 | 0.1246 | 1.0765 |
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+ | No log | 8.375 | 134 | 1.0151 | 0.0977 | 1.0120 |
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+ | No log | 8.5 | 136 | 0.9815 | 0.0716 | 0.9784 |
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+ | No log | 8.625 | 138 | 0.9817 | 0.0668 | 0.9786 |
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+ | No log | 8.75 | 140 | 0.9721 | 0.0597 | 0.9690 |
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+ | No log | 8.875 | 142 | 0.9865 | 0.0668 | 0.9834 |
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+ | No log | 9.0 | 144 | 0.9956 | 0.0716 | 0.9925 |
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+ | No log | 9.125 | 146 | 0.9824 | 0.0807 | 0.9793 |
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+ | No log | 9.25 | 148 | 0.9599 | 0.0721 | 0.9568 |
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+ | No log | 9.375 | 150 | 0.9488 | 0.0858 | 0.9456 |
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+ | No log | 9.5 | 152 | 0.9443 | 0.0858 | 0.9411 |
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+ | No log | 9.625 | 154 | 0.9603 | 0.0721 | 0.9572 |
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+ | No log | 9.75 | 156 | 0.9767 | 0.0770 | 0.9735 |
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+ | No log | 9.875 | 158 | 0.9906 | 0.0679 | 0.9874 |
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+ | No log | 10.0 | 160 | 0.9947 | 0.0679 | 0.9916 |
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  ### Framework versions
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