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arabert_cross_relevance_task2_fold5

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  1. README.md +90 -38
  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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  27. runs/Sep02_04-27-08_a09311c9b42d/events.out.tfevents.1725251229.a09311c9b42d.22.24 +3 -0
  28. training_args.bin +1 -1
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_task2_fold5
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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_task2_fold5
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.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.2016
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- - Qwk: 0.3467
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- - Mse: 0.2016
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  ## Model description
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@@ -36,45 +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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48
- | Training Loss | Epoch | Step | Validation Loss | Qwk | Mse |
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- |:-------------:|:------:|:----:|:---------------:|:------:|:------:|
50
- | No log | 0.0351 | 2 | 0.4956 | 0.1759 | 0.4956 |
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- | No log | 0.0702 | 4 | 0.3937 | 0.2727 | 0.3937 |
52
- | No log | 0.1053 | 6 | 0.3006 | 0.3553 | 0.3006 |
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- | No log | 0.1404 | 8 | 0.2240 | 0.3547 | 0.2240 |
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- | No log | 0.1754 | 10 | 0.2449 | 0.3533 | 0.2449 |
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- | No log | 0.2105 | 12 | 0.2074 | 0.3561 | 0.2074 |
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- | No log | 0.2456 | 14 | 0.2202 | 0.3186 | 0.2202 |
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- | No log | 0.2807 | 16 | 0.2130 | 0.3156 | 0.2130 |
58
- | No log | 0.3158 | 18 | 0.1954 | 0.3355 | 0.1954 |
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- | No log | 0.3509 | 20 | 0.1862 | 0.3566 | 0.1862 |
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- | No log | 0.3860 | 22 | 0.1952 | 0.3540 | 0.1952 |
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- | No log | 0.4211 | 24 | 0.2114 | 0.3598 | 0.2114 |
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- | No log | 0.4561 | 26 | 0.2080 | 0.3590 | 0.2080 |
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- | No log | 0.4912 | 28 | 0.2035 | 0.3620 | 0.2035 |
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- | No log | 0.5263 | 30 | 0.1922 | 0.3522 | 0.1922 |
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- | No log | 0.5614 | 32 | 0.1859 | 0.3539 | 0.1859 |
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- | No log | 0.5965 | 34 | 0.1885 | 0.3548 | 0.1885 |
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- | No log | 0.6316 | 36 | 0.1940 | 0.3539 | 0.1940 |
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- | No log | 0.6667 | 38 | 0.1965 | 0.3539 | 0.1965 |
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- | No log | 0.7018 | 40 | 0.1998 | 0.3529 | 0.1998 |
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- | No log | 0.7368 | 42 | 0.2035 | 0.3519 | 0.2035 |
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- | No log | 0.7719 | 44 | 0.2046 | 0.3509 | 0.2046 |
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- | No log | 0.8070 | 46 | 0.2050 | 0.3499 | 0.2050 |
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- | No log | 0.8421 | 48 | 0.2060 | 0.3509 | 0.2060 |
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- | No log | 0.8772 | 50 | 0.2059 | 0.3499 | 0.2059 |
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- | No log | 0.9123 | 52 | 0.2044 | 0.3489 | 0.2044 |
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- | No log | 0.9474 | 54 | 0.2026 | 0.3467 | 0.2026 |
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- | No log | 0.9825 | 56 | 0.2016 | 0.3467 | 0.2016 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions
 
3
  tags:
4
  - generated_from_trainer
5
  model-index:
6
+ - name: arabert_cross_relevance_task2_fold4
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_task2_fold4
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: 0.4006
18
+ - Qwk: 0.2250
19
+ - Mse: 0.4006
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 | 0.125 | 2 | 1.1063 | 0.0234 | 1.1063 |
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+ | No log | 0.25 | 4 | 0.4473 | 0.1039 | 0.4473 |
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+ | No log | 0.375 | 6 | 0.4088 | 0.2073 | 0.4088 |
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+ | No log | 0.5 | 8 | 0.4319 | 0.2351 | 0.4319 |
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+ | No log | 0.625 | 10 | 0.2875 | 0.2401 | 0.2875 |
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+ | No log | 0.75 | 12 | 0.2836 | 0.2194 | 0.2836 |
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+ | No log | 0.875 | 14 | 0.3021 | 0.2575 | 0.3021 |
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+ | No log | 1.0 | 16 | 0.2942 | 0.2831 | 0.2942 |
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+ | No log | 1.125 | 18 | 0.3155 | 0.2508 | 0.3155 |
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+ | No log | 1.25 | 20 | 0.2964 | 0.2787 | 0.2964 |
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+ | No log | 1.375 | 22 | 0.2774 | 0.2820 | 0.2774 |
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+ | No log | 1.5 | 24 | 0.2398 | 0.3029 | 0.2398 |
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+ | No log | 1.625 | 26 | 0.2524 | 0.2501 | 0.2524 |
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+ | No log | 1.75 | 28 | 0.2680 | 0.2390 | 0.2680 |
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+ | No log | 1.875 | 30 | 0.2581 | 0.2579 | 0.2581 |
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+ | No log | 2.0 | 32 | 0.2540 | 0.2787 | 0.2540 |
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+ | No log | 2.125 | 34 | 0.2836 | 0.3308 | 0.2836 |
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+ | No log | 2.25 | 36 | 0.3870 | 0.2114 | 0.3870 |
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+ | No log | 2.375 | 38 | 0.4205 | 0.2269 | 0.4205 |
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+ | No log | 2.5 | 40 | 0.3210 | 0.2236 | 0.3210 |
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+ | No log | 2.625 | 42 | 0.2478 | 0.4116 | 0.2478 |
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+ | No log | 2.75 | 44 | 0.2382 | 0.3767 | 0.2382 |
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+ | No log | 2.875 | 46 | 0.2494 | 0.2579 | 0.2494 |
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+ | No log | 3.0 | 48 | 0.3000 | 0.2553 | 0.3000 |
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+ | No log | 3.125 | 50 | 0.3533 | 0.2028 | 0.3533 |
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+ | No log | 3.25 | 52 | 0.3681 | 0.2209 | 0.3681 |
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+ | No log | 3.375 | 54 | 0.3235 | 0.2270 | 0.3235 |
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+ | No log | 3.5 | 56 | 0.2844 | 0.2648 | 0.2844 |
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+ | No log | 3.625 | 58 | 0.2941 | 0.2428 | 0.2941 |
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+ | No log | 3.75 | 60 | 0.3737 | 0.2222 | 0.3737 |
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+ | No log | 3.875 | 62 | 0.4306 | 0.2146 | 0.4306 |
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+ | No log | 4.0 | 64 | 0.4279 | 0.2146 | 0.4279 |
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+ | No log | 4.125 | 66 | 0.3959 | 0.2155 | 0.3959 |
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+ | No log | 4.25 | 68 | 0.3136 | 0.2441 | 0.3136 |
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+ | No log | 4.375 | 70 | 0.2972 | 0.2593 | 0.2972 |
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+ | No log | 4.5 | 72 | 0.2889 | 0.2677 | 0.2889 |
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+ | No log | 4.625 | 74 | 0.3100 | 0.2489 | 0.3100 |
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+ | No log | 4.75 | 76 | 0.3614 | 0.2425 | 0.3614 |
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+ | No log | 4.875 | 78 | 0.3949 | 0.2337 | 0.3949 |
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+ | No log | 5.0 | 80 | 0.4746 | 0.1752 | 0.4746 |
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+ | No log | 5.125 | 82 | 0.4462 | 0.1969 | 0.4462 |
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+ | No log | 5.25 | 84 | 0.3424 | 0.2572 | 0.3424 |
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+ | No log | 5.375 | 86 | 0.3171 | 0.2798 | 0.3171 |
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+ | No log | 5.5 | 88 | 0.3687 | 0.2452 | 0.3687 |
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+ | No log | 5.625 | 90 | 0.4496 | 0.1969 | 0.4496 |
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+ | No log | 5.75 | 92 | 0.4134 | 0.2126 | 0.4134 |
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+ | No log | 5.875 | 94 | 0.3763 | 0.2172 | 0.3763 |
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+ | No log | 6.0 | 96 | 0.3924 | 0.2106 | 0.3924 |
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+ | No log | 6.125 | 98 | 0.3918 | 0.2106 | 0.3918 |
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+ | No log | 6.25 | 100 | 0.4398 | 0.2029 | 0.4398 |
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+ | No log | 6.375 | 102 | 0.5008 | 0.1879 | 0.5008 |
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+ | No log | 6.5 | 104 | 0.4898 | 0.1781 | 0.4898 |
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+ | No log | 6.625 | 106 | 0.4198 | 0.2218 | 0.4198 |
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+ | No log | 6.75 | 108 | 0.3476 | 0.2243 | 0.3476 |
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+ | No log | 6.875 | 110 | 0.3538 | 0.2243 | 0.3538 |
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+ | No log | 7.0 | 112 | 0.4262 | 0.2163 | 0.4262 |
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+ | No log | 7.125 | 114 | 0.4667 | 0.1909 | 0.4667 |
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+ | No log | 7.25 | 116 | 0.4562 | 0.1881 | 0.4562 |
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+ | No log | 7.375 | 118 | 0.4023 | 0.2163 | 0.4023 |
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+ | No log | 7.5 | 120 | 0.3664 | 0.2169 | 0.3664 |
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+ | No log | 7.625 | 122 | 0.3487 | 0.2346 | 0.3487 |
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+ | No log | 7.75 | 124 | 0.3715 | 0.2262 | 0.3715 |
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+ | No log | 7.875 | 126 | 0.4267 | 0.2035 | 0.4267 |
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+ | No log | 8.0 | 128 | 0.5126 | 0.1714 | 0.5126 |
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+ | No log | 8.125 | 130 | 0.5465 | 0.1609 | 0.5465 |
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+ | No log | 8.25 | 132 | 0.5097 | 0.1661 | 0.5097 |
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+ | No log | 8.375 | 134 | 0.4320 | 0.2006 | 0.4320 |
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+ | No log | 8.5 | 136 | 0.3786 | 0.2290 | 0.3786 |
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+ | No log | 8.625 | 138 | 0.3721 | 0.2216 | 0.3721 |
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+ | No log | 8.75 | 140 | 0.3867 | 0.2177 | 0.3867 |
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+ | No log | 8.875 | 142 | 0.4094 | 0.2086 | 0.4094 |
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+ | No log | 9.0 | 144 | 0.4304 | 0.2070 | 0.4304 |
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+ | No log | 9.125 | 146 | 0.4412 | 0.2070 | 0.4412 |
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+ | No log | 9.25 | 148 | 0.4352 | 0.2160 | 0.4352 |
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+ | No log | 9.375 | 150 | 0.4157 | 0.2250 | 0.4157 |
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+ | No log | 9.5 | 152 | 0.4008 | 0.2250 | 0.4008 |
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+ | No log | 9.625 | 154 | 0.3937 | 0.2223 | 0.3937 |
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+ | No log | 9.75 | 156 | 0.3953 | 0.2223 | 0.3953 |
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+ | No log | 9.875 | 158 | 0.3987 | 0.2250 | 0.3987 |
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+ | No log | 10.0 | 160 | 0.4006 | 0.2250 | 0.4006 |
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