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arabert_cross_relevance_task1_fold4

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  1. README.md +85 -40
  2. model.safetensors +1 -1
  3. runs/Sep02_02-03-55_a09311c9b42d/events.out.tfevents.1725242637.a09311c9b42d.22.0 +3 -0
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  7. runs/Sep02_02-27-39_a09311c9b42d/events.out.tfevents.1725244060.a09311c9b42d.22.4 +3 -0
  8. runs/Sep02_02-27-39_a09311c9b42d/events.out.tfevents.1725244717.a09311c9b42d.22.5 +3 -0
  9. runs/Sep02_02-38-39_a09311c9b42d/events.out.tfevents.1725244720.a09311c9b42d.22.6 +3 -0
  10. runs/Sep02_02-38-39_a09311c9b42d/events.out.tfevents.1725245477.a09311c9b42d.22.7 +3 -0
  11. runs/Sep02_02-51-19_a09311c9b42d/events.out.tfevents.1725245480.a09311c9b42d.22.8 +3 -0
  12. 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_relevance_task1_fold4
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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_relevance_task1_fold4
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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: 0.2814
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- - Qwk: 0.1577
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- - Mse: 0.2814
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  ## Model description
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@@ -36,47 +36,92 @@ 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 | 0.0328 | 2 | 0.5567 | -0.0320 | 0.5567 |
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- | No log | 0.0656 | 4 | 0.5564 | -0.0102 | 0.5564 |
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- | No log | 0.0984 | 6 | 0.5081 | 0.0304 | 0.5081 |
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- | No log | 0.1311 | 8 | 0.4677 | 0.0304 | 0.4677 |
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- | No log | 0.1639 | 10 | 0.4282 | 0.0400 | 0.4282 |
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- | No log | 0.1967 | 12 | 0.4239 | 0.0496 | 0.4239 |
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- | No log | 0.2295 | 14 | 0.4171 | 0.0384 | 0.4171 |
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- | No log | 0.2623 | 16 | 0.3868 | 0.0496 | 0.3868 |
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- | No log | 0.2951 | 18 | 0.3678 | 0.0690 | 0.3678 |
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- | No log | 0.3279 | 20 | 0.3448 | 0.0596 | 0.3448 |
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- | No log | 0.3607 | 22 | 0.3295 | 0.0877 | 0.3295 |
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- | No log | 0.3934 | 24 | 0.3190 | 0.0877 | 0.3190 |
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- | No log | 0.4262 | 26 | 0.3166 | 0.0969 | 0.3166 |
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- | No log | 0.4590 | 28 | 0.3135 | 0.0969 | 0.3135 |
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- | No log | 0.4918 | 30 | 0.3075 | 0.0969 | 0.3075 |
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- | No log | 0.5246 | 32 | 0.3014 | 0.1139 | 0.3014 |
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- | No log | 0.5574 | 34 | 0.2971 | 0.1139 | 0.2971 |
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- | No log | 0.5902 | 36 | 0.2957 | 0.1048 | 0.2957 |
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- | No log | 0.6230 | 38 | 0.2937 | 0.1048 | 0.2937 |
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- | No log | 0.6557 | 40 | 0.2888 | 0.1139 | 0.2888 |
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- | No log | 0.6885 | 42 | 0.2867 | 0.1139 | 0.2867 |
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- | No log | 0.7213 | 44 | 0.2857 | 0.1139 | 0.2857 |
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- | No log | 0.7541 | 46 | 0.2847 | 0.1321 | 0.2847 |
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- | No log | 0.7869 | 48 | 0.2833 | 0.1577 | 0.2833 |
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- | No log | 0.8197 | 50 | 0.2826 | 0.1577 | 0.2826 |
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- | No log | 0.8525 | 52 | 0.2822 | 0.1577 | 0.2822 |
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- | No log | 0.8852 | 54 | 0.2805 | 0.1577 | 0.2805 |
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- | No log | 0.9180 | 56 | 0.2810 | 0.1667 | 0.2810 |
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- | No log | 0.9508 | 58 | 0.2816 | 0.1667 | 0.2816 |
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- | No log | 0.9836 | 60 | 0.2814 | 0.1577 | 0.2814 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions
 
3
  tags:
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  - generated_from_trainer
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  model-index:
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+ - name: arabert_cross_relevance_task1_fold3
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  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_relevance_task1_fold3
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.
16
  It achieves the following results on the evaluation set:
17
+ - Loss: 0.2800
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+ - Qwk: 0.4057
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+ - Mse: 0.2800
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21
  ## Model description
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36
 
37
  The following hyperparameters were used during training:
38
  - 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
43
  - lr_scheduler_type: linear
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+ - num_epochs: 10
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46
  ### 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 | 0.4841 | 0.2229 | 0.4841 |
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+ | No log | 0.2667 | 4 | 0.4548 | 0.1951 | 0.4548 |
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+ | No log | 0.4 | 6 | 0.3736 | 0.2470 | 0.3736 |
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+ | No log | 0.5333 | 8 | 0.3640 | 0.2129 | 0.3640 |
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+ | No log | 0.6667 | 10 | 0.3899 | 0.1839 | 0.3899 |
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+ | No log | 0.8 | 12 | 0.3649 | 0.1986 | 0.3649 |
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+ | No log | 0.9333 | 14 | 0.3192 | 0.3366 | 0.3192 |
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+ | No log | 1.0667 | 16 | 0.3134 | 0.3522 | 0.3134 |
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+ | No log | 1.2 | 18 | 0.2989 | 0.3399 | 0.2989 |
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+ | No log | 1.3333 | 20 | 0.3038 | 0.3248 | 0.3038 |
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+ | No log | 1.4667 | 22 | 0.3097 | 0.3239 | 0.3097 |
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+ | No log | 1.6 | 24 | 0.2998 | 0.3258 | 0.2998 |
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+ | No log | 1.7333 | 26 | 0.2810 | 0.3516 | 0.2810 |
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+ | No log | 1.8667 | 28 | 0.2789 | 0.3522 | 0.2789 |
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+ | No log | 2.0 | 30 | 0.2800 | 0.3509 | 0.2800 |
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+ | No log | 2.1333 | 32 | 0.2906 | 0.3375 | 0.2906 |
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+ | No log | 2.2667 | 34 | 0.3124 | 0.2959 | 0.3124 |
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+ | No log | 2.4 | 36 | 0.3211 | 0.3784 | 0.3211 |
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+ | No log | 2.5333 | 38 | 0.3001 | 0.3428 | 0.3001 |
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+ | No log | 2.6667 | 40 | 0.2852 | 0.3575 | 0.2852 |
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+ | No log | 2.8 | 42 | 0.2865 | 0.3529 | 0.2865 |
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+ | No log | 2.9333 | 44 | 0.2806 | 0.3509 | 0.2806 |
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+ | No log | 3.0667 | 46 | 0.2874 | 0.3391 | 0.2874 |
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+ | No log | 3.2 | 48 | 0.3047 | 0.3615 | 0.3047 |
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+ | No log | 3.3333 | 50 | 0.3111 | 0.3705 | 0.3111 |
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+ | No log | 3.4667 | 52 | 0.3016 | 0.3428 | 0.3016 |
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+ | No log | 3.6 | 54 | 0.2849 | 0.3391 | 0.2849 |
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+ | No log | 3.7333 | 56 | 0.2726 | 0.3502 | 0.2726 |
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+ | No log | 3.8667 | 58 | 0.2737 | 0.3515 | 0.2737 |
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+ | No log | 4.0 | 60 | 0.2771 | 0.3515 | 0.2771 |
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+ | No log | 4.1333 | 62 | 0.2716 | 0.3509 | 0.2716 |
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+ | No log | 4.2667 | 64 | 0.2745 | 0.3480 | 0.2745 |
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+ | No log | 4.4 | 66 | 0.2815 | 0.3431 | 0.2815 |
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+ | No log | 4.5333 | 68 | 0.2772 | 0.3599 | 0.2772 |
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+ | No log | 4.6667 | 70 | 0.2685 | 0.3637 | 0.2685 |
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+ | No log | 4.8 | 72 | 0.2627 | 0.3536 | 0.2627 |
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+ | No log | 4.9333 | 74 | 0.2621 | 0.3549 | 0.2621 |
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+ | No log | 5.0667 | 76 | 0.2604 | 0.3640 | 0.2604 |
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+ | No log | 5.2 | 78 | 0.2644 | 0.3909 | 0.2644 |
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+ | No log | 5.3333 | 80 | 0.2834 | 0.4063 | 0.2834 |
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+ | No log | 5.4667 | 82 | 0.2855 | 0.3857 | 0.2855 |
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+ | No log | 5.6 | 84 | 0.2777 | 0.3709 | 0.2777 |
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+ | No log | 5.7333 | 86 | 0.2703 | 0.3543 | 0.2703 |
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+ | No log | 5.8667 | 88 | 0.2731 | 0.3495 | 0.2731 |
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+ | No log | 6.0 | 90 | 0.2756 | 0.3509 | 0.2756 |
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+ | No log | 6.1333 | 92 | 0.2782 | 0.3538 | 0.2782 |
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+ | No log | 6.2667 | 94 | 0.2856 | 0.3720 | 0.2856 |
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+ | No log | 6.4 | 96 | 0.2950 | 0.4113 | 0.2950 |
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+ | No log | 6.5333 | 98 | 0.3066 | 0.4735 | 0.3066 |
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+ | No log | 6.6667 | 100 | 0.2982 | 0.4566 | 0.2982 |
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+ | No log | 6.8 | 102 | 0.2915 | 0.4196 | 0.2915 |
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+ | No log | 6.9333 | 104 | 0.2806 | 0.3842 | 0.2806 |
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+ | No log | 7.0667 | 106 | 0.2757 | 0.3868 | 0.2757 |
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+ | No log | 7.2 | 108 | 0.2790 | 0.3895 | 0.2790 |
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+ | No log | 7.3333 | 110 | 0.2776 | 0.3868 | 0.2776 |
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+ | No log | 7.4667 | 112 | 0.2706 | 0.3605 | 0.2706 |
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+ | No log | 7.6 | 114 | 0.2683 | 0.3518 | 0.2683 |
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+ | No log | 7.7333 | 116 | 0.2688 | 0.3518 | 0.2688 |
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+ | No log | 7.8667 | 118 | 0.2706 | 0.3617 | 0.2706 |
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+ | No log | 8.0 | 120 | 0.2740 | 0.3712 | 0.2740 |
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+ | No log | 8.1333 | 122 | 0.2770 | 0.3712 | 0.2770 |
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+ | No log | 8.2667 | 124 | 0.2813 | 0.3756 | 0.2813 |
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+ | No log | 8.4 | 126 | 0.2862 | 0.3730 | 0.2862 |
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+ | No log | 8.5333 | 128 | 0.2926 | 0.4157 | 0.2926 |
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+ | No log | 8.6667 | 130 | 0.2956 | 0.4209 | 0.2956 |
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+ | No log | 8.8 | 132 | 0.2928 | 0.4211 | 0.2928 |
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+ | No log | 8.9333 | 134 | 0.2870 | 0.4052 | 0.2870 |
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+ | No log | 9.0667 | 136 | 0.2834 | 0.3945 | 0.2834 |
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+ | No log | 9.2 | 138 | 0.2828 | 0.4002 | 0.2828 |
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+ | No log | 9.3333 | 140 | 0.2815 | 0.3952 | 0.2815 |
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+ | No log | 9.4667 | 142 | 0.2814 | 0.4057 | 0.2814 |
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+ | No log | 9.6 | 144 | 0.2807 | 0.4057 | 0.2807 |
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+ | No log | 9.7333 | 146 | 0.2801 | 0.4057 | 0.2801 |
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+ | No log | 9.8667 | 148 | 0.2799 | 0.4057 | 0.2799 |
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+ | No log | 10.0 | 150 | 0.2800 | 0.4057 | 0.2800 |
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