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arabert_cross_relevance_task4_fold3

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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_fold3
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_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:
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- - Loss: 0.3149
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- - Qwk: 0.3219
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- - Mse: 0.3149
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  ## Model description
22
 
@@ -36,49 +36,107 @@ 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 | 0.6456 | 0.1075 | 0.6456 |
51
- | No log | 0.0615 | 4 | 0.4575 | 0.2193 | 0.4575 |
52
- | No log | 0.0923 | 6 | 0.4674 | 0.2535 | 0.4674 |
53
- | No log | 0.1231 | 8 | 0.5729 | 0.1524 | 0.5729 |
54
- | No log | 0.1538 | 10 | 0.3886 | 0.2903 | 0.3886 |
55
- | No log | 0.1846 | 12 | 0.4032 | 0.2047 | 0.4032 |
56
- | No log | 0.2154 | 14 | 0.4025 | 0.1193 | 0.4025 |
57
- | No log | 0.2462 | 16 | 0.3963 | 0.0956 | 0.3963 |
58
- | No log | 0.2769 | 18 | 0.3978 | 0.1280 | 0.3978 |
59
- | No log | 0.3077 | 20 | 0.3869 | 0.1979 | 0.3869 |
60
- | No log | 0.3385 | 22 | 0.3693 | 0.2273 | 0.3693 |
61
- | No log | 0.3692 | 24 | 0.3556 | 0.2505 | 0.3556 |
62
- | No log | 0.4 | 26 | 0.3417 | 0.2365 | 0.3417 |
63
- | No log | 0.4308 | 28 | 0.3385 | 0.2571 | 0.3385 |
64
- | No log | 0.4615 | 30 | 0.3433 | 0.2434 | 0.3433 |
65
- | No log | 0.4923 | 32 | 0.3471 | 0.2503 | 0.3471 |
66
- | No log | 0.5231 | 34 | 0.3537 | 0.2776 | 0.3537 |
67
- | No log | 0.5538 | 36 | 0.3590 | 0.2907 | 0.3590 |
68
- | No log | 0.5846 | 38 | 0.3558 | 0.2586 | 0.3558 |
69
- | No log | 0.6154 | 40 | 0.3484 | 0.2718 | 0.3484 |
70
- | No log | 0.6462 | 42 | 0.3430 | 0.2811 | 0.3430 |
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- | No log | 0.6769 | 44 | 0.3356 | 0.2875 | 0.3356 |
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- | No log | 0.7077 | 46 | 0.3309 | 0.2875 | 0.3309 |
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- | No log | 0.7385 | 48 | 0.3268 | 0.2889 | 0.3268 |
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- | No log | 0.7692 | 50 | 0.3226 | 0.3165 | 0.3226 |
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- | No log | 0.8 | 52 | 0.3203 | 0.3229 | 0.3203 |
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- | No log | 0.8308 | 54 | 0.3180 | 0.3288 | 0.3180 |
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- | No log | 0.8615 | 56 | 0.3175 | 0.3279 | 0.3175 |
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- | No log | 0.8923 | 58 | 0.3168 | 0.3279 | 0.3168 |
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- | No log | 0.9231 | 60 | 0.3158 | 0.3219 | 0.3158 |
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- | No log | 0.9538 | 62 | 0.3151 | 0.3219 | 0.3151 |
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- | No log | 0.9846 | 64 | 0.3149 | 0.3219 | 0.3149 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
82
 
83
 
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  ### Framework versions
 
3
  tags:
4
  - generated_from_trainer
5
  model-index:
6
+ - name: arabert_cross_relevance_task4_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_task4_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: 0.4752
18
+ - Qwk: 0.1093
19
+ - Mse: 0.4759
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
+ |:-------------:|:------:|:----:|:---------------:|:-------:|:------:|
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+ | No log | 0.1111 | 2 | 0.5785 | 0.0868 | 0.5777 |
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+ | No log | 0.2222 | 4 | 0.2943 | -0.0164 | 0.2947 |
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+ | No log | 0.3333 | 6 | 0.3987 | 0.0024 | 0.3993 |
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+ | No log | 0.4444 | 8 | 0.3899 | 0.0752 | 0.3904 |
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+ | No log | 0.5556 | 10 | 0.3473 | -0.0042 | 0.3477 |
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+ | No log | 0.6667 | 12 | 0.4204 | 0.0370 | 0.4209 |
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+ | No log | 0.7778 | 14 | 0.5631 | -0.0284 | 0.5638 |
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+ | No log | 0.8889 | 16 | 0.5554 | -0.0028 | 0.5561 |
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+ | No log | 1.0 | 18 | 0.5578 | 0.0426 | 0.5584 |
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+ | No log | 1.1111 | 20 | 0.4455 | 0.0325 | 0.4461 |
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+ | No log | 1.2222 | 22 | 0.3963 | 0.0368 | 0.3969 |
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+ | No log | 1.3333 | 24 | 0.3919 | 0.0243 | 0.3924 |
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+ | No log | 1.4444 | 26 | 0.4089 | 0.0665 | 0.4094 |
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+ | No log | 1.5556 | 28 | 0.3918 | 0.0619 | 0.3923 |
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+ | No log | 1.6667 | 30 | 0.4355 | -0.0079 | 0.4360 |
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+ | No log | 1.7778 | 32 | 0.4965 | 0.1166 | 0.4971 |
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+ | No log | 1.8889 | 34 | 0.5320 | -0.0186 | 0.5326 |
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+ | No log | 2.0 | 36 | 0.5879 | 0.0536 | 0.5885 |
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+ | No log | 2.1111 | 38 | 0.5920 | 0.1117 | 0.5926 |
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+ | No log | 2.2222 | 40 | 0.5586 | 0.1740 | 0.5592 |
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+ | No log | 2.3333 | 42 | 0.4887 | 0.0570 | 0.4892 |
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+ | No log | 2.4444 | 44 | 0.4523 | 0.0512 | 0.4527 |
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+ | No log | 2.5556 | 46 | 0.4295 | 0.0633 | 0.4299 |
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+ | No log | 2.6667 | 48 | 0.4439 | 0.0643 | 0.4444 |
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+ | No log | 2.7778 | 50 | 0.4579 | -0.0142 | 0.4585 |
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+ | No log | 2.8889 | 52 | 0.4404 | 0.0594 | 0.4409 |
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+ | No log | 3.0 | 54 | 0.4585 | 0.0325 | 0.4590 |
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+ | No log | 3.1111 | 56 | 0.5216 | 0.1088 | 0.5222 |
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+ | No log | 3.2222 | 58 | 0.5552 | 0.0747 | 0.5559 |
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+ | No log | 3.3333 | 60 | 0.5458 | 0.1373 | 0.5465 |
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+ | No log | 3.4444 | 62 | 0.4947 | 0.1774 | 0.4953 |
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+ | No log | 3.5556 | 64 | 0.4605 | 0.0419 | 0.4611 |
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+ | No log | 3.6667 | 66 | 0.4341 | -0.0514 | 0.4346 |
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+ | No log | 3.7778 | 68 | 0.4227 | -0.0500 | 0.4232 |
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+ | No log | 3.8889 | 70 | 0.4149 | -0.0016 | 0.4154 |
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+ | No log | 4.0 | 72 | 0.4133 | 0.0112 | 0.4138 |
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+ | No log | 4.1111 | 74 | 0.4299 | 0.0681 | 0.4304 |
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+ | No log | 4.2222 | 76 | 0.4431 | 0.0874 | 0.4437 |
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+ | No log | 4.3333 | 78 | 0.4609 | 0.1618 | 0.4615 |
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+ | No log | 4.4444 | 80 | 0.4845 | 0.1449 | 0.4851 |
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+ | No log | 4.5556 | 82 | 0.5171 | 0.1801 | 0.5178 |
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+ | No log | 4.6667 | 84 | 0.5429 | 0.0638 | 0.5436 |
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+ | No log | 4.7778 | 86 | 0.5295 | 0.1054 | 0.5302 |
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+ | No log | 4.8889 | 88 | 0.4873 | 0.1361 | 0.4880 |
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+ | No log | 5.0 | 90 | 0.4385 | 0.0551 | 0.4391 |
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+ | No log | 5.1111 | 92 | 0.4189 | 0.0586 | 0.4195 |
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+ | No log | 5.2222 | 94 | 0.4360 | 0.0730 | 0.4366 |
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+ | No log | 5.3333 | 96 | 0.4771 | 0.0422 | 0.4778 |
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+ | No log | 5.4444 | 98 | 0.4940 | 0.0473 | 0.4947 |
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+ | No log | 5.5556 | 100 | 0.5040 | 0.0525 | 0.5047 |
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+ | No log | 5.6667 | 102 | 0.4813 | 0.0030 | 0.4819 |
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+ | No log | 5.7778 | 104 | 0.4381 | 0.0917 | 0.4387 |
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+ | No log | 5.8889 | 106 | 0.3938 | -0.0553 | 0.3943 |
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+ | No log | 6.0 | 108 | 0.3964 | -0.0475 | 0.3969 |
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+ | No log | 6.1111 | 110 | 0.4237 | 0.0059 | 0.4242 |
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+ | No log | 6.2222 | 112 | 0.4695 | 0.1283 | 0.4701 |
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+ | No log | 6.3333 | 114 | 0.4933 | 0.0923 | 0.4940 |
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+ | No log | 6.4444 | 116 | 0.5089 | 0.0578 | 0.5096 |
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+ | No log | 6.5556 | 118 | 0.5097 | 0.0886 | 0.5105 |
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+ | No log | 6.6667 | 120 | 0.4867 | 0.0724 | 0.4874 |
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+ | No log | 6.7778 | 122 | 0.4496 | 0.0831 | 0.4502 |
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+ | No log | 6.8889 | 124 | 0.4192 | 0.0197 | 0.4198 |
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+ | No log | 7.0 | 126 | 0.4075 | 0.0496 | 0.4081 |
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+ | No log | 7.1111 | 128 | 0.4043 | 0.0369 | 0.4049 |
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+ | No log | 7.2222 | 130 | 0.4164 | 0.0326 | 0.4170 |
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+ | No log | 7.3333 | 132 | 0.4361 | 0.0815 | 0.4367 |
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+ | No log | 7.4444 | 134 | 0.4517 | 0.1068 | 0.4524 |
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+ | No log | 7.5556 | 136 | 0.4513 | 0.1209 | 0.4519 |
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+ | No log | 7.6667 | 138 | 0.4452 | 0.1056 | 0.4458 |
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+ | No log | 7.7778 | 140 | 0.4514 | 0.0743 | 0.4520 |
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+ | No log | 7.8889 | 142 | 0.4671 | 0.1472 | 0.4677 |
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+ | No log | 8.0 | 144 | 0.4902 | 0.0969 | 0.4909 |
122
+ | No log | 8.1111 | 146 | 0.5000 | -0.0230 | 0.5007 |
123
+ | No log | 8.2222 | 148 | 0.4999 | -0.0028 | 0.5006 |
124
+ | No log | 8.3333 | 150 | 0.4924 | 0.0374 | 0.4931 |
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+ | No log | 8.4444 | 152 | 0.4849 | 0.0857 | 0.4855 |
126
+ | No log | 8.5556 | 154 | 0.4790 | 0.0857 | 0.4796 |
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+ | No log | 8.6667 | 156 | 0.4774 | 0.0857 | 0.4780 |
128
+ | No log | 8.7778 | 158 | 0.4814 | 0.1004 | 0.4820 |
129
+ | No log | 8.8889 | 160 | 0.4916 | 0.0866 | 0.4923 |
130
+ | No log | 9.0 | 162 | 0.4998 | 0.0525 | 0.5005 |
131
+ | No log | 9.1111 | 164 | 0.5009 | 0.0676 | 0.5016 |
132
+ | No log | 9.2222 | 166 | 0.4971 | 0.0676 | 0.4978 |
133
+ | No log | 9.3333 | 168 | 0.4903 | 0.1166 | 0.4910 |
134
+ | No log | 9.4444 | 170 | 0.4831 | 0.1641 | 0.4838 |
135
+ | No log | 9.5556 | 172 | 0.4811 | 0.1832 | 0.4818 |
136
+ | No log | 9.6667 | 174 | 0.4780 | 0.1534 | 0.4786 |
137
+ | No log | 9.7778 | 176 | 0.4767 | 0.1239 | 0.4774 |
138
+ | No log | 9.8889 | 178 | 0.4754 | 0.1093 | 0.4760 |
139
+ | No log | 10.0 | 180 | 0.4752 | 0.1093 | 0.4759 |
140
 
141
 
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  ### Framework versions
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