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arabert_cross_relevance_task4_fold1

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  1. README.md +95 -42
  2. model.safetensors +1 -1
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README.md CHANGED
@@ -3,20 +3,20 @@ base_model: aubmindlab/bert-base-arabertv02
3
  tags:
4
  - generated_from_trainer
5
  model-index:
6
- - name: arabert_cross_relevance_task4_fold1
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_fold1
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: 0.1659
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- - Qwk: 0.0402
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- - Mse: 0.1659
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  ## Model description
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@@ -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
 
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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 | 2.0522 | -0.0055 | 2.0522 |
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- | No log | 0.0615 | 4 | 0.6665 | -0.0084 | 0.6665 |
52
- | No log | 0.0923 | 6 | 0.2290 | 0.0207 | 0.2290 |
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- | No log | 0.1231 | 8 | 0.1690 | 0.0796 | 0.1690 |
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- | No log | 0.1538 | 10 | 0.2100 | 0.0199 | 0.2100 |
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- | No log | 0.1846 | 12 | 0.4380 | 0.0228 | 0.4380 |
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- | No log | 0.2154 | 14 | 0.4146 | 0.0114 | 0.4146 |
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- | No log | 0.2462 | 16 | 0.4672 | 0.0164 | 0.4672 |
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- | No log | 0.2769 | 18 | 0.4548 | 0.0082 | 0.4548 |
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- | No log | 0.3077 | 20 | 0.3092 | 0.0166 | 0.3092 |
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- | No log | 0.3385 | 22 | 0.1656 | 0.0373 | 0.1656 |
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- | No log | 0.3692 | 24 | 0.1443 | 0.0155 | 0.1443 |
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- | No log | 0.4 | 26 | 0.1375 | 0.0344 | 0.1375 |
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- | No log | 0.4308 | 28 | 0.1319 | 0.0250 | 0.1319 |
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- | No log | 0.4615 | 30 | 0.1415 | 0.0270 | 0.1415 |
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- | No log | 0.4923 | 32 | 0.1730 | 0.0185 | 0.1730 |
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- | No log | 0.5231 | 34 | 0.2033 | 0.0185 | 0.2033 |
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- | No log | 0.5538 | 36 | 0.2320 | 0.0166 | 0.2320 |
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- | No log | 0.5846 | 38 | 0.2349 | 0.0149 | 0.2349 |
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- | No log | 0.6154 | 40 | 0.2136 | 0.0165 | 0.2136 |
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- | No log | 0.6462 | 42 | 0.1798 | 0.0165 | 0.1798 |
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- | No log | 0.6769 | 44 | 0.1596 | 0.0175 | 0.1596 |
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- | No log | 0.7077 | 46 | 0.1554 | 0.0243 | 0.1554 |
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- | No log | 0.7385 | 48 | 0.1612 | 0.0316 | 0.1612 |
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- | No log | 0.7692 | 50 | 0.1628 | 0.0261 | 0.1628 |
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- | No log | 0.8 | 52 | 0.1699 | 0.0317 | 0.1699 |
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- | No log | 0.8308 | 54 | 0.1702 | 0.0284 | 0.1702 |
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- | No log | 0.8615 | 56 | 0.1679 | 0.0334 | 0.1679 |
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- | No log | 0.8923 | 58 | 0.1678 | 0.0334 | 0.1678 |
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- | No log | 0.9231 | 60 | 0.1646 | 0.0436 | 0.1646 |
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- | No log | 0.9538 | 62 | 0.1648 | 0.0402 | 0.1648 |
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- | No log | 0.9846 | 64 | 0.1659 | 0.0402 | 0.1659 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
82
 
83
 
84
  ### Framework versions
 
3
  tags:
4
  - generated_from_trainer
5
  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:
17
+ - Loss: 0.2736
18
+ - Qwk: 0.1560
19
+ - Mse: 0.2738
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 | 0.5899 | 0.0303 | 0.5899 |
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+ | No log | 0.2353 | 4 | 0.2991 | 0.0083 | 0.2993 |
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+ | No log | 0.3529 | 6 | 0.2856 | 0.0046 | 0.2859 |
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+ | No log | 0.4706 | 8 | 0.3724 | 0.0918 | 0.3727 |
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+ | No log | 0.5882 | 10 | 0.3677 | 0.1010 | 0.3680 |
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+ | No log | 0.7059 | 12 | 0.2967 | 0.0745 | 0.2971 |
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+ | No log | 0.8235 | 14 | 0.2878 | 0.0745 | 0.2883 |
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+ | No log | 0.9412 | 16 | 0.3092 | 0.0849 | 0.3099 |
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+ | No log | 1.0588 | 18 | 0.3111 | 0.0769 | 0.3118 |
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+ | No log | 1.1765 | 20 | 0.3278 | 0.0860 | 0.3286 |
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+ | No log | 1.2941 | 22 | 0.3356 | 0.0940 | 0.3363 |
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+ | No log | 1.4118 | 24 | 0.3182 | 0.0930 | 0.3188 |
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+ | No log | 1.5294 | 26 | 0.2840 | 0.0711 | 0.2844 |
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+ | No log | 1.6471 | 28 | 0.2640 | 0.0745 | 0.2644 |
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+ | No log | 1.7647 | 30 | 0.2617 | 0.0787 | 0.2620 |
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+ | No log | 1.8824 | 32 | 0.2721 | 0.0686 | 0.2724 |
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+ | No log | 2.0 | 34 | 0.2784 | 0.0709 | 0.2787 |
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+ | No log | 2.1176 | 36 | 0.2850 | 0.1325 | 0.2852 |
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+ | No log | 2.2353 | 38 | 0.2912 | 0.2051 | 0.2915 |
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+ | No log | 2.3529 | 40 | 0.2922 | 0.1733 | 0.2925 |
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+ | No log | 2.4706 | 42 | 0.2846 | 0.1093 | 0.2850 |
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+ | No log | 2.5882 | 44 | 0.2920 | 0.1049 | 0.2924 |
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+ | No log | 2.7059 | 46 | 0.3062 | 0.1101 | 0.3066 |
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+ | No log | 2.8235 | 48 | 0.2956 | 0.1049 | 0.2961 |
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+ | No log | 2.9412 | 50 | 0.2664 | 0.1066 | 0.2668 |
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+ | No log | 3.0588 | 52 | 0.2583 | 0.1197 | 0.2587 |
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+ | No log | 3.1765 | 54 | 0.2638 | 0.1594 | 0.2642 |
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+ | No log | 3.2941 | 56 | 0.2611 | 0.1408 | 0.2615 |
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+ | No log | 3.4118 | 58 | 0.2742 | 0.1087 | 0.2747 |
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+ | No log | 3.5294 | 60 | 0.2867 | 0.0956 | 0.2872 |
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+ | No log | 3.6471 | 62 | 0.3015 | 0.0985 | 0.3019 |
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+ | No log | 3.7647 | 64 | 0.2991 | 0.1076 | 0.2995 |
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+ | No log | 3.8824 | 66 | 0.2717 | 0.1219 | 0.2721 |
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+ | No log | 4.0 | 68 | 0.2625 | 0.1787 | 0.2628 |
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+ | No log | 4.1176 | 70 | 0.2648 | 0.2139 | 0.2651 |
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+ | No log | 4.2353 | 72 | 0.2608 | 0.1889 | 0.2611 |
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+ | No log | 4.3529 | 74 | 0.2596 | 0.1230 | 0.2599 |
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+ | No log | 4.4706 | 76 | 0.2657 | 0.1072 | 0.2660 |
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+ | No log | 4.5882 | 78 | 0.2691 | 0.1064 | 0.2695 |
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+ | No log | 4.7059 | 80 | 0.2573 | 0.0987 | 0.2577 |
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+ | No log | 4.8235 | 82 | 0.2467 | 0.1026 | 0.2470 |
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+ | No log | 4.9412 | 84 | 0.2538 | 0.1374 | 0.2541 |
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+ | No log | 5.0588 | 86 | 0.2632 | 0.1541 | 0.2635 |
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+ | No log | 5.1765 | 88 | 0.2699 | 0.1482 | 0.2702 |
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+ | No log | 5.2941 | 90 | 0.2684 | 0.1464 | 0.2687 |
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+ | No log | 5.4118 | 92 | 0.2643 | 0.1446 | 0.2646 |
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+ | No log | 5.5294 | 94 | 0.2663 | 0.1381 | 0.2665 |
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+ | No log | 5.6471 | 96 | 0.2594 | 0.1117 | 0.2597 |
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+ | No log | 5.7647 | 98 | 0.2596 | 0.1043 | 0.2599 |
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+ | No log | 5.8824 | 100 | 0.2557 | 0.1095 | 0.2559 |
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+ | No log | 6.0 | 102 | 0.2552 | 0.1192 | 0.2555 |
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+ | No log | 6.1176 | 104 | 0.2623 | 0.1286 | 0.2626 |
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+ | No log | 6.2353 | 106 | 0.2589 | 0.1349 | 0.2592 |
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+ | No log | 6.3529 | 108 | 0.2591 | 0.1493 | 0.2593 |
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+ | No log | 6.4706 | 110 | 0.2623 | 0.1697 | 0.2626 |
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+ | No log | 6.5882 | 112 | 0.2713 | 0.1744 | 0.2716 |
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+ | No log | 6.7059 | 114 | 0.2740 | 0.1744 | 0.2743 |
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+ | No log | 6.8235 | 116 | 0.2753 | 0.1499 | 0.2756 |
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+ | No log | 6.9412 | 118 | 0.2729 | 0.1471 | 0.2732 |
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+ | No log | 7.0588 | 120 | 0.2685 | 0.1437 | 0.2688 |
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+ | No log | 7.1765 | 122 | 0.2665 | 0.1388 | 0.2667 |
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+ | No log | 7.2941 | 124 | 0.2587 | 0.1432 | 0.2589 |
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+ | No log | 7.4118 | 126 | 0.2538 | 0.1376 | 0.2541 |
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+ | No log | 7.5294 | 128 | 0.2554 | 0.1388 | 0.2557 |
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+ | No log | 7.6471 | 130 | 0.2570 | 0.1592 | 0.2572 |
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+ | No log | 7.7647 | 132 | 0.2582 | 0.1593 | 0.2584 |
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+ | No log | 7.8824 | 134 | 0.2619 | 0.1575 | 0.2621 |
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+ | No log | 8.0 | 136 | 0.2676 | 0.1543 | 0.2678 |
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+ | No log | 8.1176 | 138 | 0.2711 | 0.1419 | 0.2714 |
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+ | No log | 8.2353 | 140 | 0.2745 | 0.1388 | 0.2747 |
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+ | No log | 8.3529 | 142 | 0.2729 | 0.1388 | 0.2731 |
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+ | No log | 8.4706 | 144 | 0.2716 | 0.1325 | 0.2718 |
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+ | No log | 8.5882 | 146 | 0.2731 | 0.1295 | 0.2734 |
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+ | No log | 8.7059 | 148 | 0.2726 | 0.1287 | 0.2729 |
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+ | No log | 8.8235 | 150 | 0.2748 | 0.1306 | 0.2751 |
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+ | No log | 8.9412 | 152 | 0.2760 | 0.1400 | 0.2762 |
126
+ | No log | 9.0588 | 154 | 0.2751 | 0.1400 | 0.2754 |
127
+ | No log | 9.1765 | 156 | 0.2728 | 0.1478 | 0.2731 |
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+ | No log | 9.2941 | 158 | 0.2721 | 0.1478 | 0.2723 |
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+ | No log | 9.4118 | 160 | 0.2716 | 0.1478 | 0.2718 |
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+ | No log | 9.5294 | 162 | 0.2714 | 0.1478 | 0.2717 |
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+ | No log | 9.6471 | 164 | 0.2722 | 0.1478 | 0.2725 |
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+ | No log | 9.7647 | 166 | 0.2731 | 0.1560 | 0.2733 |
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+ | No log | 9.8824 | 168 | 0.2734 | 0.1560 | 0.2736 |
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+ | No log | 10.0 | 170 | 0.2736 | 0.1560 | 0.2738 |
135
 
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  ### Framework versions
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