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arabert_cross_relevance_task4_fold0

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  1. README.md +93 -40
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README.md CHANGED
@@ -3,20 +3,20 @@ base_model: aubmindlab/bert-base-arabertv02
3
  tags:
4
  - generated_from_trainer
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  model-index:
6
- - name: arabert_cross_relevance_task4_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_relevance_task4_fold0
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:
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- - Loss: 0.2479
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- - Qwk: 0.1137
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- - Mse: 0.2477
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  ## Model description
22
 
@@ -36,49 +36,102 @@ More information needed
36
 
37
  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
42
  - 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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46
  ### Training results
47
 
48
  | Training Loss | Epoch | Step | Validation Loss | Qwk | Mse |
49
  |:-------------:|:------:|:----:|:---------------:|:------:|:------:|
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- | No log | 0.0308 | 2 | 1.1704 | 0.0068 | 1.1689 |
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- | No log | 0.0615 | 4 | 0.3625 | 0.0496 | 0.3618 |
52
- | No log | 0.0923 | 6 | 0.2641 | 0.0297 | 0.2635 |
53
- | No log | 0.1231 | 8 | 0.2513 | 0.0073 | 0.2507 |
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- | No log | 0.1538 | 10 | 0.3032 | 0.0512 | 0.3025 |
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- | No log | 0.1846 | 12 | 0.3827 | 0.0703 | 0.3818 |
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- | No log | 0.2154 | 14 | 0.3771 | 0.0767 | 0.3763 |
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- | No log | 0.2462 | 16 | 0.3026 | 0.0809 | 0.3019 |
58
- | No log | 0.2769 | 18 | 0.2590 | 0.0646 | 0.2586 |
59
- | No log | 0.3077 | 20 | 0.2674 | 0.0745 | 0.2668 |
60
- | No log | 0.3385 | 22 | 0.2762 | 0.0992 | 0.2757 |
61
- | No log | 0.3692 | 24 | 0.2855 | 0.1225 | 0.2852 |
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- | No log | 0.4 | 26 | 0.3271 | 0.1089 | 0.3269 |
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- | No log | 0.4308 | 28 | 0.3800 | 0.1124 | 0.3799 |
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- | No log | 0.4615 | 30 | 0.4123 | 0.0941 | 0.4122 |
65
- | No log | 0.4923 | 32 | 0.4381 | 0.0968 | 0.4379 |
66
- | No log | 0.5231 | 34 | 0.4126 | 0.1072 | 0.4124 |
67
- | No log | 0.5538 | 36 | 0.3850 | 0.1134 | 0.3848 |
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- | No log | 0.5846 | 38 | 0.3976 | 0.1200 | 0.3974 |
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- | No log | 0.6154 | 40 | 0.4201 | 0.1208 | 0.4198 |
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- | No log | 0.6462 | 42 | 0.3902 | 0.1237 | 0.3899 |
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- | No log | 0.6769 | 44 | 0.3376 | 0.1125 | 0.3373 |
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- | No log | 0.7077 | 46 | 0.3133 | 0.1172 | 0.3131 |
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- | No log | 0.7385 | 48 | 0.3111 | 0.1181 | 0.3109 |
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- | No log | 0.7692 | 50 | 0.2963 | 0.1221 | 0.2960 |
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- | No log | 0.8 | 52 | 0.2785 | 0.1201 | 0.2783 |
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- | No log | 0.8308 | 54 | 0.2692 | 0.1314 | 0.2691 |
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- | No log | 0.8615 | 56 | 0.2596 | 0.1243 | 0.2594 |
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- | No log | 0.8923 | 58 | 0.2565 | 0.1191 | 0.2563 |
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- | No log | 0.9231 | 60 | 0.2527 | 0.1137 | 0.2525 |
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- | No log | 0.9538 | 62 | 0.2495 | 0.1137 | 0.2494 |
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- | No log | 0.9846 | 64 | 0.2479 | 0.1137 | 0.2477 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
82
 
83
 
84
  ### Framework versions
 
3
  tags:
4
  - generated_from_trainer
5
  model-index:
6
+ - name: arabert_cross_relevance_task3_fold6
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_relevance_task3_fold6
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: 0.3958
18
+ - Qwk: 0.2096
19
+ - Mse: 0.3959
20
 
21
  ## Model description
22
 
 
36
 
37
  The following hyperparameters were used during training:
38
  - learning_rate: 2e-05
39
+ - train_batch_size: 64
40
+ - eval_batch_size: 64
41
  - seed: 42
42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
43
  - lr_scheduler_type: linear
44
+ - num_epochs: 10
45
 
46
  ### Training results
47
 
48
  | Training Loss | Epoch | Step | Validation Loss | Qwk | Mse |
49
  |:-------------:|:------:|:----:|:---------------:|:------:|:------:|
50
+ | No log | 0.1176 | 2 | 0.7510 | 0.0098 | 0.7490 |
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+ | No log | 0.2353 | 4 | 0.3906 | 0.1162 | 0.3902 |
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+ | No log | 0.3529 | 6 | 0.3053 | 0.1347 | 0.3057 |
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+ | No log | 0.4706 | 8 | 0.2972 | 0.1520 | 0.2976 |
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+ | No log | 0.5882 | 10 | 0.2828 | 0.1830 | 0.2831 |
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+ | No log | 0.7059 | 12 | 0.2698 | 0.1906 | 0.2703 |
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+ | No log | 0.8235 | 14 | 0.2743 | 0.1500 | 0.2750 |
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+ | No log | 0.9412 | 16 | 0.2742 | 0.1578 | 0.2747 |
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+ | No log | 1.0588 | 18 | 0.3079 | 0.1726 | 0.3083 |
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+ | No log | 1.1765 | 20 | 0.3022 | 0.1999 | 0.3025 |
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+ | No log | 1.2941 | 22 | 0.2720 | 0.2049 | 0.2724 |
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+ | No log | 1.4118 | 24 | 0.2712 | 0.2178 | 0.2717 |
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+ | No log | 1.5294 | 26 | 0.2820 | 0.2018 | 0.2823 |
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+ | No log | 1.6471 | 28 | 0.2988 | 0.2137 | 0.2990 |
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+ | No log | 1.7647 | 30 | 0.2801 | 0.2099 | 0.2803 |
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+ | No log | 1.8824 | 32 | 0.2536 | 0.2155 | 0.2541 |
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+ | No log | 2.0 | 34 | 0.2547 | 0.2222 | 0.2553 |
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+ | No log | 2.1176 | 36 | 0.2817 | 0.1893 | 0.2821 |
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+ | No log | 2.2353 | 38 | 0.3173 | 0.2127 | 0.3175 |
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+ | No log | 2.3529 | 40 | 0.2805 | 0.1991 | 0.2808 |
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+ | No log | 2.4706 | 42 | 0.2617 | 0.2112 | 0.2624 |
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+ | No log | 2.5882 | 44 | 0.2662 | 0.2183 | 0.2670 |
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+ | No log | 2.7059 | 46 | 0.2560 | 0.2109 | 0.2565 |
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+ | No log | 2.8235 | 48 | 0.3002 | 0.2083 | 0.3005 |
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+ | No log | 2.9412 | 50 | 0.3062 | 0.2127 | 0.3065 |
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+ | No log | 3.0588 | 52 | 0.2753 | 0.1995 | 0.2757 |
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+ | No log | 3.1765 | 54 | 0.2479 | 0.2057 | 0.2485 |
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+ | No log | 3.2941 | 56 | 0.2470 | 0.1860 | 0.2476 |
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+ | No log | 3.4118 | 58 | 0.2610 | 0.2099 | 0.2614 |
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+ | No log | 3.5294 | 60 | 0.2690 | 0.2044 | 0.2693 |
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+ | No log | 3.6471 | 62 | 0.2641 | 0.2067 | 0.2645 |
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+ | No log | 3.7647 | 64 | 0.2712 | 0.1995 | 0.2715 |
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+ | No log | 3.8824 | 66 | 0.2789 | 0.1943 | 0.2792 |
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+ | No log | 4.0 | 68 | 0.2918 | 0.2127 | 0.2920 |
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+ | No log | 4.1176 | 70 | 0.2717 | 0.2038 | 0.2720 |
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+ | No log | 4.2353 | 72 | 0.2866 | 0.2127 | 0.2868 |
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+ | No log | 4.3529 | 74 | 0.2850 | 0.2127 | 0.2852 |
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+ | No log | 4.4706 | 76 | 0.2771 | 0.2292 | 0.2774 |
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+ | No log | 4.5882 | 78 | 0.2687 | 0.1915 | 0.2690 |
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+ | No log | 4.7059 | 80 | 0.2758 | 0.2044 | 0.2761 |
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+ | No log | 4.8235 | 82 | 0.3101 | 0.2211 | 0.3103 |
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+ | No log | 4.9412 | 84 | 0.3572 | 0.2110 | 0.3573 |
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+ | No log | 5.0588 | 86 | 0.3906 | 0.1858 | 0.3906 |
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+ | No log | 5.1765 | 88 | 0.3591 | 0.1982 | 0.3592 |
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+ | No log | 5.2941 | 90 | 0.3170 | 0.2140 | 0.3173 |
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+ | No log | 5.4118 | 92 | 0.3098 | 0.2140 | 0.3102 |
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+ | No log | 5.5294 | 94 | 0.3073 | 0.2048 | 0.3077 |
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+ | No log | 5.6471 | 96 | 0.3304 | 0.2001 | 0.3307 |
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+ | No log | 5.7647 | 98 | 0.3825 | 0.2103 | 0.3825 |
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+ | No log | 5.8824 | 100 | 0.3978 | 0.1979 | 0.3978 |
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+ | No log | 6.0 | 102 | 0.3627 | 0.2110 | 0.3629 |
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+ | No log | 6.1176 | 104 | 0.3352 | 0.1985 | 0.3354 |
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+ | No log | 6.2353 | 106 | 0.3174 | 0.2127 | 0.3177 |
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+ | No log | 6.3529 | 108 | 0.3418 | 0.2070 | 0.3421 |
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+ | No log | 6.4706 | 110 | 0.3437 | 0.1982 | 0.3439 |
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+ | No log | 6.5882 | 112 | 0.3452 | 0.1982 | 0.3454 |
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+ | No log | 6.7059 | 114 | 0.3485 | 0.2070 | 0.3487 |
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+ | No log | 6.8235 | 116 | 0.3713 | 0.1979 | 0.3714 |
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+ | No log | 6.9412 | 118 | 0.3854 | 0.1858 | 0.3855 |
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+ | No log | 7.0588 | 120 | 0.3950 | 0.1821 | 0.3949 |
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+ | No log | 7.1765 | 122 | 0.3832 | 0.1858 | 0.3832 |
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+ | No log | 7.2941 | 124 | 0.3695 | 0.2019 | 0.3697 |
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+ | No log | 7.4118 | 126 | 0.3763 | 0.2058 | 0.3764 |
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+ | No log | 7.5294 | 128 | 0.3884 | 0.1898 | 0.3885 |
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+ | No log | 7.6471 | 130 | 0.4063 | 0.1785 | 0.4064 |
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+ | No log | 7.7647 | 132 | 0.3900 | 0.1780 | 0.3901 |
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+ | No log | 7.8824 | 134 | 0.3822 | 0.1739 | 0.3823 |
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+ | No log | 8.0 | 136 | 0.3725 | 0.1856 | 0.3726 |
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+ | No log | 8.1176 | 138 | 0.3559 | 0.1854 | 0.3560 |
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+ | No log | 8.2353 | 140 | 0.3576 | 0.2023 | 0.3578 |
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+ | No log | 8.3529 | 142 | 0.3825 | 0.1977 | 0.3826 |
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+ | No log | 8.4706 | 144 | 0.3960 | 0.2015 | 0.3961 |
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+ | No log | 8.5882 | 146 | 0.3877 | 0.2015 | 0.3877 |
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+ | No log | 8.7059 | 148 | 0.3846 | 0.2096 | 0.3847 |
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+ | No log | 8.8235 | 150 | 0.3711 | 0.2058 | 0.3712 |
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+ | No log | 8.9412 | 152 | 0.3592 | 0.2103 | 0.3594 |
126
+ | No log | 9.0588 | 154 | 0.3526 | 0.2103 | 0.3529 |
127
+ | No log | 9.1765 | 156 | 0.3597 | 0.2141 | 0.3598 |
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+ | No log | 9.2941 | 158 | 0.3711 | 0.2058 | 0.3712 |
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+ | No log | 9.4118 | 160 | 0.3827 | 0.2096 | 0.3828 |
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+ | No log | 9.5294 | 162 | 0.3867 | 0.2096 | 0.3867 |
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+ | No log | 9.6471 | 164 | 0.3912 | 0.2096 | 0.3912 |
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+ | No log | 9.7647 | 166 | 0.3942 | 0.2096 | 0.3942 |
133
+ | No log | 9.8824 | 168 | 0.3960 | 0.2096 | 0.3960 |
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+ | No log | 10.0 | 170 | 0.3958 | 0.2096 | 0.3959 |
135
 
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  ### Framework versions
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