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arabert_cross_relevance_task5_fold0

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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_task5_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_task5_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: 0.2821
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- - Qwk: 0.0624
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- - Mse: 0.2820
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  ## Model description
22
 
@@ -36,45 +36,107 @@ 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
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 | 0.0351 | 2 | 1.4820 | -0.0183 | 1.4821 |
51
- | No log | 0.0702 | 4 | 0.6837 | 0.0391 | 0.6838 |
52
- | No log | 0.1053 | 6 | 0.3465 | 0.0562 | 0.3463 |
53
- | No log | 0.1404 | 8 | 0.4761 | -0.0323 | 0.4757 |
54
- | No log | 0.1754 | 10 | 0.4401 | -0.0362 | 0.4394 |
55
- | No log | 0.2105 | 12 | 0.3074 | -0.0097 | 0.3072 |
56
- | No log | 0.2456 | 14 | 0.2597 | 0.0101 | 0.2597 |
57
- | No log | 0.2807 | 16 | 0.2629 | -0.0073 | 0.2629 |
58
- | No log | 0.3158 | 18 | 0.2753 | 0.0010 | 0.2751 |
59
- | No log | 0.3509 | 20 | 0.2789 | 0.0091 | 0.2788 |
60
- | No log | 0.3860 | 22 | 0.2807 | 0.0055 | 0.2806 |
61
- | No log | 0.4211 | 24 | 0.2657 | 0.0245 | 0.2656 |
62
- | No log | 0.4561 | 26 | 0.2518 | 0.0116 | 0.2517 |
63
- | No log | 0.4912 | 28 | 0.2590 | 0.0323 | 0.2590 |
64
- | No log | 0.5263 | 30 | 0.2649 | 0.0144 | 0.2648 |
65
- | No log | 0.5614 | 32 | 0.2691 | 0.0036 | 0.2689 |
66
- | No log | 0.5965 | 34 | 0.2672 | 0.0071 | 0.2671 |
67
- | No log | 0.6316 | 36 | 0.2663 | 0.0356 | 0.2661 |
68
- | No log | 0.6667 | 38 | 0.2656 | 0.0628 | 0.2655 |
69
- | No log | 0.7018 | 40 | 0.2632 | 0.0478 | 0.2631 |
70
- | No log | 0.7368 | 42 | 0.2641 | 0.0517 | 0.2640 |
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- | No log | 0.7719 | 44 | 0.2671 | 0.0414 | 0.2671 |
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- | No log | 0.8070 | 46 | 0.2735 | 0.0598 | 0.2735 |
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- | No log | 0.8421 | 48 | 0.2820 | 0.0558 | 0.2820 |
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- | No log | 0.8772 | 50 | 0.2862 | 0.0624 | 0.2861 |
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- | No log | 0.9123 | 52 | 0.2852 | 0.0624 | 0.2851 |
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- | No log | 0.9474 | 54 | 0.2831 | 0.0624 | 0.2831 |
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- | No log | 0.9825 | 56 | 0.2821 | 0.0624 | 0.2820 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
78
 
79
 
80
  ### Framework versions
 
3
  tags:
4
  - generated_from_trainer
5
  model-index:
6
+ - name: arabert_cross_relevance_task4_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_task4_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: 0.3394
18
+ - Qwk: 0.1601
19
+ - Mse: 0.3398
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 | 0.1111 | 2 | 0.4458 | 0.0318 | 0.4461 |
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+ | No log | 0.2222 | 4 | 0.3469 | 0.0319 | 0.3472 |
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+ | No log | 0.3333 | 6 | 0.3536 | 0.0805 | 0.3537 |
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+ | No log | 0.4444 | 8 | 0.3107 | 0.0717 | 0.3106 |
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+ | No log | 0.5556 | 10 | 0.2972 | 0.1151 | 0.2971 |
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+ | No log | 0.6667 | 12 | 0.2762 | 0.1226 | 0.2762 |
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+ | No log | 0.7778 | 14 | 0.2644 | 0.1492 | 0.2647 |
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+ | No log | 0.8889 | 16 | 0.2552 | 0.1559 | 0.2557 |
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+ | No log | 1.0 | 18 | 0.2658 | 0.2351 | 0.2661 |
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+ | No log | 1.1111 | 20 | 0.2702 | 0.2761 | 0.2706 |
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+ | No log | 1.2222 | 22 | 0.2662 | 0.2796 | 0.2669 |
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+ | No log | 1.3333 | 24 | 0.2499 | 0.2669 | 0.2508 |
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+ | No log | 1.4444 | 26 | 0.2460 | 0.2651 | 0.2468 |
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+ | No log | 1.5556 | 28 | 0.2523 | 0.2545 | 0.2531 |
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+ | No log | 1.6667 | 30 | 0.2554 | 0.2137 | 0.2561 |
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+ | No log | 1.7778 | 32 | 0.2471 | 0.2220 | 0.2478 |
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+ | No log | 1.8889 | 34 | 0.2416 | 0.2899 | 0.2423 |
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+ | No log | 2.0 | 36 | 0.2485 | 0.2753 | 0.2491 |
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+ | No log | 2.1111 | 38 | 0.2427 | 0.2134 | 0.2433 |
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+ | No log | 2.2222 | 40 | 0.2377 | 0.2055 | 0.2383 |
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+ | No log | 2.3333 | 42 | 0.2333 | 0.2092 | 0.2338 |
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+ | No log | 2.4444 | 44 | 0.2390 | 0.2332 | 0.2394 |
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+ | No log | 2.5556 | 46 | 0.2482 | 0.2477 | 0.2487 |
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+ | No log | 2.6667 | 48 | 0.2585 | 0.2256 | 0.2591 |
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+ | No log | 2.7778 | 50 | 0.2626 | 0.2812 | 0.2633 |
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+ | No log | 2.8889 | 52 | 0.2502 | 0.2684 | 0.2508 |
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+ | No log | 3.0 | 54 | 0.2402 | 0.1962 | 0.2407 |
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+ | No log | 3.1111 | 56 | 0.2434 | 0.1883 | 0.2439 |
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+ | No log | 3.2222 | 58 | 0.2516 | 0.2024 | 0.2522 |
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+ | No log | 3.3333 | 60 | 0.2671 | 0.3187 | 0.2678 |
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+ | No log | 3.4444 | 62 | 0.2665 | 0.2324 | 0.2672 |
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+ | No log | 3.5556 | 64 | 0.2719 | 0.1977 | 0.2725 |
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+ | No log | 3.6667 | 66 | 0.2689 | 0.2130 | 0.2695 |
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+ | No log | 3.7778 | 68 | 0.2612 | 0.2140 | 0.2618 |
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+ | No log | 3.8889 | 70 | 0.2566 | 0.2395 | 0.2572 |
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+ | No log | 4.0 | 72 | 0.2553 | 0.2583 | 0.2560 |
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+ | No log | 4.1111 | 74 | 0.2604 | 0.2476 | 0.2610 |
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+ | No log | 4.2222 | 76 | 0.2643 | 0.2402 | 0.2649 |
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+ | No log | 4.3333 | 78 | 0.2719 | 0.2220 | 0.2725 |
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+ | No log | 4.4444 | 80 | 0.2816 | 0.1895 | 0.2822 |
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+ | No log | 4.5556 | 82 | 0.2776 | 0.2106 | 0.2783 |
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+ | No log | 4.6667 | 84 | 0.2758 | 0.2275 | 0.2765 |
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+ | No log | 4.7778 | 86 | 0.2876 | 0.2033 | 0.2882 |
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+ | No log | 4.8889 | 88 | 0.3127 | 0.1941 | 0.3132 |
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+ | No log | 5.0 | 90 | 0.3256 | 0.1643 | 0.3260 |
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+ | No log | 5.1111 | 92 | 0.3061 | 0.1895 | 0.3065 |
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+ | No log | 5.2222 | 94 | 0.2811 | 0.2186 | 0.2816 |
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+ | No log | 5.3333 | 96 | 0.2823 | 0.2186 | 0.2827 |
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+ | No log | 5.4444 | 98 | 0.2910 | 0.2137 | 0.2913 |
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+ | No log | 5.5556 | 100 | 0.3094 | 0.2076 | 0.3096 |
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+ | No log | 5.6667 | 102 | 0.3152 | 0.2118 | 0.3154 |
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+ | No log | 5.7778 | 104 | 0.3477 | 0.1897 | 0.3478 |
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+ | No log | 5.8889 | 106 | 0.3597 | 0.1780 | 0.3598 |
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+ | No log | 6.0 | 108 | 0.3476 | 0.1780 | 0.3479 |
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+ | No log | 6.1111 | 110 | 0.3267 | 0.1992 | 0.3272 |
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+ | No log | 6.2222 | 112 | 0.3089 | 0.2125 | 0.3095 |
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+ | No log | 6.3333 | 114 | 0.3128 | 0.1908 | 0.3134 |
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+ | No log | 6.4444 | 116 | 0.3211 | 0.1742 | 0.3215 |
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+ | No log | 6.5556 | 118 | 0.3339 | 0.1590 | 0.3343 |
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+ | No log | 6.6667 | 120 | 0.3109 | 0.1741 | 0.3113 |
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+ | No log | 6.7778 | 122 | 0.2827 | 0.2060 | 0.2832 |
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+ | No log | 6.8889 | 124 | 0.2767 | 0.2060 | 0.2772 |
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+ | No log | 7.0 | 126 | 0.2730 | 0.2130 | 0.2736 |
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+ | No log | 7.1111 | 128 | 0.2806 | 0.2009 | 0.2812 |
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+ | No log | 7.2222 | 130 | 0.2954 | 0.2098 | 0.2959 |
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+ | No log | 7.3333 | 132 | 0.3020 | 0.2033 | 0.3025 |
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+ | No log | 7.4444 | 134 | 0.3007 | 0.2098 | 0.3012 |
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+ | No log | 7.5556 | 136 | 0.2958 | 0.2054 | 0.2964 |
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+ | No log | 7.6667 | 138 | 0.3086 | 0.1781 | 0.3091 |
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+ | No log | 7.7778 | 140 | 0.3217 | 0.1623 | 0.3222 |
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+ | No log | 7.8889 | 142 | 0.3310 | 0.1677 | 0.3315 |
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+ | No log | 8.0 | 144 | 0.3269 | 0.1668 | 0.3274 |
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+ | No log | 8.1111 | 146 | 0.3173 | 0.1682 | 0.3179 |
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+ | No log | 8.2222 | 148 | 0.3173 | 0.1682 | 0.3178 |
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+ | No log | 8.3333 | 150 | 0.3261 | 0.1634 | 0.3266 |
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+ | No log | 8.4444 | 152 | 0.3255 | 0.1634 | 0.3259 |
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+ | No log | 8.5556 | 154 | 0.3229 | 0.1711 | 0.3234 |
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+ | No log | 8.6667 | 156 | 0.3219 | 0.1668 | 0.3225 |
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+ | No log | 8.7778 | 158 | 0.3264 | 0.1634 | 0.3269 |
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+ | No log | 8.8889 | 160 | 0.3314 | 0.1558 | 0.3319 |
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+ | No log | 9.0 | 162 | 0.3302 | 0.1558 | 0.3307 |
131
+ | No log | 9.1111 | 164 | 0.3292 | 0.1601 | 0.3297 |
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+ | No log | 9.2222 | 166 | 0.3320 | 0.1601 | 0.3325 |
133
+ | No log | 9.3333 | 168 | 0.3371 | 0.1601 | 0.3376 |
134
+ | No log | 9.4444 | 170 | 0.3396 | 0.1601 | 0.3400 |
135
+ | No log | 9.5556 | 172 | 0.3414 | 0.1601 | 0.3418 |
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+ | No log | 9.6667 | 174 | 0.3407 | 0.1601 | 0.3411 |
137
+ | No log | 9.7778 | 176 | 0.3400 | 0.1601 | 0.3404 |
138
+ | No log | 9.8889 | 178 | 0.3392 | 0.1601 | 0.3396 |
139
+ | No log | 10.0 | 180 | 0.3394 | 0.1601 | 0.3398 |
140
 
141
 
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  ### Framework versions
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