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arabert_cross_relevance_task3_fold2

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  1. README.md +90 -45
  2. model.safetensors +1 -1
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  36. training_args.bin +1 -1
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_task3_fold2
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_fold2
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: 0.2924
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- - Qwk: 0.0385
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- - Mse: 0.2924
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21
  ## Model description
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@@ -36,52 +36,97 @@ More information needed
36
 
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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
41
  - 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 | 0.0282 | 2 | 1.9951 | 0.0 | 1.9951 |
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- | No log | 0.0563 | 4 | 0.8321 | -0.0021 | 0.8321 |
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- | No log | 0.0845 | 6 | 0.2802 | 0.0 | 0.2802 |
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- | No log | 0.1127 | 8 | 0.4458 | 0.0625 | 0.4458 |
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- | No log | 0.1408 | 10 | 0.4881 | 0.2089 | 0.4881 |
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- | No log | 0.1690 | 12 | 0.3011 | -0.0156 | 0.3011 |
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- | No log | 0.1972 | 14 | 0.2760 | 0.0 | 0.2760 |
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- | No log | 0.2254 | 16 | 0.2997 | 0.0 | 0.2997 |
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- | No log | 0.2535 | 18 | 0.2559 | 0.0 | 0.2559 |
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- | No log | 0.2817 | 20 | 0.2551 | 0.0 | 0.2551 |
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- | No log | 0.3099 | 22 | 0.2568 | 0.0101 | 0.2568 |
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- | No log | 0.3380 | 24 | 0.2555 | 0.0 | 0.2555 |
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- | No log | 0.3662 | 26 | 0.2788 | 0.0068 | 0.2788 |
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- | No log | 0.3944 | 28 | 0.3484 | 0.1190 | 0.3484 |
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- | No log | 0.4225 | 30 | 0.4157 | 0.1667 | 0.4157 |
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- | No log | 0.4507 | 32 | 0.4046 | 0.0517 | 0.4046 |
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- | No log | 0.4789 | 34 | 0.3355 | -0.0833 | 0.3355 |
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- | No log | 0.5070 | 36 | 0.3106 | 0.0299 | 0.3106 |
68
- | No log | 0.5352 | 38 | 0.3088 | -0.0401 | 0.3088 |
69
- | No log | 0.5634 | 40 | 0.3026 | -0.0069 | 0.3026 |
70
- | No log | 0.5915 | 42 | 0.2826 | 0.0517 | 0.2826 |
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- | No log | 0.6197 | 44 | 0.2644 | 0.0306 | 0.2644 |
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- | No log | 0.6479 | 46 | 0.2643 | 0.0306 | 0.2643 |
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- | No log | 0.6761 | 48 | 0.2781 | 0.0411 | 0.2781 |
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- | No log | 0.7042 | 50 | 0.2873 | 0.0625 | 0.2873 |
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- | No log | 0.7324 | 52 | 0.3190 | -0.0039 | 0.3190 |
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- | No log | 0.7606 | 54 | 0.3488 | -0.0096 | 0.3488 |
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- | No log | 0.7887 | 56 | 0.3736 | 0.1316 | 0.3736 |
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- | No log | 0.8169 | 58 | 0.3688 | 0.1146 | 0.3688 |
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- | No log | 0.8451 | 60 | 0.3437 | 0.0238 | 0.3437 |
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- | No log | 0.8732 | 62 | 0.3162 | 0.0504 | 0.3162 |
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- | No log | 0.9014 | 64 | 0.3006 | 0.0328 | 0.3006 |
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- | No log | 0.9296 | 66 | 0.2955 | 0.0248 | 0.2955 |
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- | No log | 0.9577 | 68 | 0.2926 | 0.0385 | 0.2926 |
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- | No log | 0.9859 | 70 | 0.2924 | 0.0385 | 0.2924 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
85
 
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87
  ### Framework versions
 
3
  tags:
4
  - generated_from_trainer
5
  model-index:
6
+ - name: arabert_cross_relevance_task3_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_task3_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:
17
+ - Loss: 0.1458
18
+ - Qwk: 0.0595
19
+ - Mse: 0.1458
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 | 0.7079 | -0.0000 | 0.7079 |
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+ | No log | 0.25 | 4 | 0.1912 | 0.0157 | 0.1912 |
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+ | No log | 0.375 | 6 | 0.1659 | 0.0284 | 0.1659 |
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+ | No log | 0.5 | 8 | 0.3128 | 0.0094 | 0.3128 |
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+ | No log | 0.625 | 10 | 0.2898 | 0.0076 | 0.2898 |
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+ | No log | 0.75 | 12 | 0.2065 | 0.0185 | 0.2065 |
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+ | No log | 0.875 | 14 | 0.1447 | 0.0270 | 0.1447 |
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+ | No log | 1.0 | 16 | 0.1501 | 0.0387 | 0.1501 |
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+ | No log | 1.125 | 18 | 0.2147 | 0.0278 | 0.2147 |
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+ | No log | 1.25 | 20 | 0.2330 | 0.0260 | 0.2330 |
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+ | No log | 1.375 | 22 | 0.1773 | 0.0402 | 0.1773 |
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+ | No log | 1.5 | 24 | 0.1419 | 0.0853 | 0.1419 |
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+ | No log | 1.625 | 26 | 0.1384 | 0.0553 | 0.1384 |
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+ | No log | 1.75 | 28 | 0.1481 | 0.0342 | 0.1481 |
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+ | No log | 1.875 | 30 | 0.1586 | 0.0376 | 0.1586 |
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+ | No log | 2.0 | 32 | 0.1665 | 0.0463 | 0.1665 |
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+ | No log | 2.125 | 34 | 0.1964 | 0.0423 | 0.1964 |
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+ | No log | 2.25 | 36 | 0.1779 | 0.0511 | 0.1779 |
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+ | No log | 2.375 | 38 | 0.1542 | 0.1019 | 0.1542 |
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+ | No log | 2.5 | 40 | 0.1505 | 0.1356 | 0.1505 |
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+ | No log | 2.625 | 42 | 0.1422 | 0.1332 | 0.1422 |
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+ | No log | 2.75 | 44 | 0.1427 | 0.0769 | 0.1427 |
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+ | No log | 2.875 | 46 | 0.1755 | 0.0359 | 0.1755 |
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+ | No log | 3.0 | 48 | 0.2548 | 0.0300 | 0.2548 |
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+ | No log | 3.125 | 50 | 0.2939 | 0.0263 | 0.2939 |
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+ | No log | 3.25 | 52 | 0.2512 | 0.0263 | 0.2512 |
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+ | No log | 3.375 | 54 | 0.1646 | 0.0268 | 0.1646 |
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+ | No log | 3.5 | 56 | 0.1283 | 0.1045 | 0.1283 |
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+ | No log | 3.625 | 58 | 0.1365 | 0.1428 | 0.1365 |
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+ | No log | 3.75 | 60 | 0.1354 | 0.1127 | 0.1354 |
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+ | No log | 3.875 | 62 | 0.1424 | 0.0619 | 0.1424 |
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+ | No log | 4.0 | 64 | 0.2058 | 0.0376 | 0.2058 |
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+ | No log | 4.125 | 66 | 0.2354 | 0.0359 | 0.2354 |
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+ | No log | 4.25 | 68 | 0.1903 | 0.0376 | 0.1903 |
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+ | No log | 4.375 | 70 | 0.1417 | 0.0497 | 0.1417 |
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+ | No log | 4.5 | 72 | 0.1346 | 0.0775 | 0.1346 |
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+ | No log | 4.625 | 74 | 0.1423 | 0.0729 | 0.1423 |
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+ | No log | 4.75 | 76 | 0.1585 | 0.0451 | 0.1585 |
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+ | No log | 4.875 | 78 | 0.1582 | 0.0399 | 0.1582 |
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+ | No log | 5.0 | 80 | 0.1374 | 0.0729 | 0.1374 |
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+ | No log | 5.125 | 82 | 0.1284 | 0.1045 | 0.1284 |
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+ | No log | 5.25 | 84 | 0.1284 | 0.1110 | 0.1284 |
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+ | No log | 5.375 | 86 | 0.1307 | 0.0769 | 0.1307 |
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+ | No log | 5.5 | 88 | 0.1473 | 0.0351 | 0.1473 |
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+ | No log | 5.625 | 90 | 0.1726 | 0.0389 | 0.1726 |
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+ | No log | 5.75 | 92 | 0.1734 | 0.0441 | 0.1734 |
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+ | No log | 5.875 | 94 | 0.1544 | 0.0547 | 0.1544 |
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+ | No log | 6.0 | 96 | 0.1361 | 0.1029 | 0.1361 |
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+ | No log | 6.125 | 98 | 0.1362 | 0.1379 | 0.1362 |
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+ | No log | 6.25 | 100 | 0.1358 | 0.1551 | 0.1358 |
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+ | No log | 6.375 | 102 | 0.1338 | 0.1029 | 0.1338 |
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+ | No log | 6.5 | 104 | 0.1417 | 0.0744 | 0.1417 |
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+ | No log | 6.625 | 106 | 0.1467 | 0.0647 | 0.1467 |
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+ | No log | 6.75 | 108 | 0.1456 | 0.0627 | 0.1456 |
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+ | No log | 6.875 | 110 | 0.1429 | 0.0609 | 0.1429 |
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+ | No log | 7.0 | 112 | 0.1442 | 0.0609 | 0.1442 |
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+ | No log | 7.125 | 114 | 0.1423 | 0.0669 | 0.1423 |
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+ | No log | 7.25 | 116 | 0.1407 | 0.0554 | 0.1407 |
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+ | No log | 7.375 | 118 | 0.1417 | 0.0675 | 0.1417 |
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+ | No log | 7.5 | 120 | 0.1453 | 0.0634 | 0.1453 |
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+ | No log | 7.625 | 122 | 0.1508 | 0.0661 | 0.1508 |
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+ | No log | 7.75 | 124 | 0.1573 | 0.0603 | 0.1573 |
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+ | No log | 7.875 | 126 | 0.1579 | 0.0547 | 0.1579 |
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+ | No log | 8.0 | 128 | 0.1512 | 0.0591 | 0.1512 |
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+ | No log | 8.125 | 130 | 0.1432 | 0.0733 | 0.1432 |
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+ | No log | 8.25 | 132 | 0.1387 | 0.0861 | 0.1387 |
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+ | No log | 8.375 | 134 | 0.1376 | 0.0883 | 0.1376 |
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+ | No log | 8.5 | 136 | 0.1388 | 0.0738 | 0.1388 |
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+ | No log | 8.625 | 138 | 0.1432 | 0.0811 | 0.1432 |
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+ | No log | 8.75 | 140 | 0.1486 | 0.0669 | 0.1486 |
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+ | No log | 8.875 | 142 | 0.1523 | 0.0591 | 0.1523 |
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+ | No log | 9.0 | 144 | 0.1538 | 0.0610 | 0.1538 |
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+ | No log | 9.125 | 146 | 0.1533 | 0.0534 | 0.1533 |
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+ | No log | 9.25 | 148 | 0.1515 | 0.0592 | 0.1515 |
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+ | No log | 9.375 | 150 | 0.1492 | 0.0574 | 0.1492 |
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+ | No log | 9.5 | 152 | 0.1465 | 0.0534 | 0.1465 |
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+ | No log | 9.625 | 154 | 0.1454 | 0.0595 | 0.1454 |
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+ | No log | 9.75 | 156 | 0.1453 | 0.0595 | 0.1453 |
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+ | No log | 9.875 | 158 | 0.1457 | 0.0595 | 0.1457 |
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+ | No log | 10.0 | 160 | 0.1458 | 0.0595 | 0.1458 |
130
 
131
 
132
  ### Framework versions
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