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arabert_cross_relevance_task6_fold1

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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_task6_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_task6_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: 0.1984
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- - Qwk: 0.0339
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- - Mse: 0.1984
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  ## Model description
22
 
@@ -36,47 +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
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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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  ### Training results
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- | Training Loss | Epoch | Step | Validation Loss | Qwk | Mse |
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- |:-------------:|:------:|:----:|:---------------:|:------:|:------:|
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- | No log | 0.0328 | 2 | 0.3596 | 0.0131 | 0.3596 |
51
- | No log | 0.0656 | 4 | 0.2224 | 0.0161 | 0.2224 |
52
- | No log | 0.0984 | 6 | 0.1576 | 0.0089 | 0.1576 |
53
- | No log | 0.1311 | 8 | 0.1621 | 0.0033 | 0.1621 |
54
- | No log | 0.1639 | 10 | 0.2030 | 0.0166 | 0.2030 |
55
- | No log | 0.1967 | 12 | 0.2309 | 0.0166 | 0.2309 |
56
- | No log | 0.2295 | 14 | 0.2066 | 0.0166 | 0.2066 |
57
- | No log | 0.2623 | 16 | 0.1537 | 0.0199 | 0.1537 |
58
- | No log | 0.2951 | 18 | 0.1474 | 0.0216 | 0.1474 |
59
- | No log | 0.3279 | 20 | 0.1395 | 0.0048 | 0.1395 |
60
- | No log | 0.3607 | 22 | 0.1473 | 0.0108 | 0.1473 |
61
- | No log | 0.3934 | 24 | 0.1611 | 0.0166 | 0.1611 |
62
- | No log | 0.4262 | 26 | 0.1923 | 0.0254 | 0.1923 |
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- | No log | 0.4590 | 28 | 0.1777 | 0.0254 | 0.1777 |
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- | No log | 0.4918 | 30 | 0.1692 | 0.0339 | 0.1692 |
65
- | No log | 0.5246 | 32 | 0.1642 | 0.0251 | 0.1642 |
66
- | No log | 0.5574 | 34 | 0.1604 | 0.0251 | 0.1604 |
67
- | No log | 0.5902 | 36 | 0.1534 | 0.0165 | 0.1534 |
68
- | No log | 0.6230 | 38 | 0.1506 | 0.0165 | 0.1506 |
69
- | No log | 0.6557 | 40 | 0.1565 | 0.0185 | 0.1565 |
70
- | No log | 0.6885 | 42 | 0.1643 | 0.0185 | 0.1643 |
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- | No log | 0.7213 | 44 | 0.1753 | 0.0185 | 0.1753 |
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- | No log | 0.7541 | 46 | 0.1925 | 0.0254 | 0.1925 |
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- | No log | 0.7869 | 48 | 0.2044 | 0.0254 | 0.2044 |
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- | No log | 0.8197 | 50 | 0.2135 | 0.0254 | 0.2135 |
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- | No log | 0.8525 | 52 | 0.2141 | 0.0339 | 0.2141 |
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- | No log | 0.8852 | 54 | 0.2135 | 0.0339 | 0.2135 |
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- | No log | 0.9180 | 56 | 0.2071 | 0.0339 | 0.2071 |
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- | No log | 0.9508 | 58 | 0.2007 | 0.0339 | 0.2007 |
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- | No log | 0.9836 | 60 | 0.1984 | 0.0339 | 0.1984 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
80
 
81
 
82
  ### Framework versions
 
3
  tags:
4
  - generated_from_trainer
5
  model-index:
6
+ - name: arabert_cross_relevance_task6_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_task6_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: 0.2663
18
+ - Qwk: 0.1037
19
+ - Mse: 0.2666
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
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+ - num_epochs: 10
45
 
46
  ### Training results
47
 
48
+ | Training Loss | Epoch | Step | Validation Loss | Qwk | Mse |
49
+ |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
50
+ | No log | 0.125 | 2 | 0.6210 | 0.0393 | 0.6211 |
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+ | No log | 0.25 | 4 | 0.2908 | 0.1547 | 0.2908 |
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+ | No log | 0.375 | 6 | 0.2874 | 0.0578 | 0.2874 |
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+ | No log | 0.5 | 8 | 0.4029 | 0.0871 | 0.4030 |
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+ | No log | 0.625 | 10 | 0.3376 | 0.0431 | 0.3380 |
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+ | No log | 0.75 | 12 | 0.2435 | 0.0180 | 0.2438 |
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+ | No log | 0.875 | 14 | 0.2523 | 0.0961 | 0.2524 |
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+ | No log | 1.0 | 16 | 0.2567 | 0.1388 | 0.2568 |
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+ | No log | 1.125 | 18 | 0.2419 | 0.0918 | 0.2421 |
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+ | No log | 1.25 | 20 | 0.2428 | 0.1144 | 0.2430 |
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+ | No log | 1.375 | 22 | 0.2547 | 0.1135 | 0.2549 |
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+ | No log | 1.5 | 24 | 0.2577 | 0.1333 | 0.2580 |
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+ | No log | 1.625 | 26 | 0.2622 | 0.1251 | 0.2625 |
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+ | No log | 1.75 | 28 | 0.2584 | 0.1527 | 0.2587 |
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+ | No log | 1.875 | 30 | 0.2572 | 0.1427 | 0.2574 |
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+ | No log | 2.0 | 32 | 0.2550 | 0.1355 | 0.2552 |
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+ | No log | 2.125 | 34 | 0.2553 | 0.1382 | 0.2554 |
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+ | No log | 2.25 | 36 | 0.2485 | 0.1178 | 0.2486 |
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+ | No log | 2.375 | 38 | 0.2485 | 0.0965 | 0.2487 |
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+ | No log | 2.5 | 40 | 0.2463 | 0.0999 | 0.2465 |
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+ | No log | 2.625 | 42 | 0.2473 | 0.1607 | 0.2475 |
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+ | No log | 2.75 | 44 | 0.2547 | 0.2134 | 0.2549 |
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+ | No log | 2.875 | 46 | 0.2547 | 0.1888 | 0.2549 |
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+ | No log | 3.0 | 48 | 0.2540 | 0.1555 | 0.2542 |
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+ | No log | 3.125 | 50 | 0.2562 | 0.1232 | 0.2565 |
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+ | No log | 3.25 | 52 | 0.2605 | 0.1037 | 0.2607 |
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+ | No log | 3.375 | 54 | 0.2527 | 0.1245 | 0.2529 |
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+ | No log | 3.5 | 56 | 0.2460 | 0.1932 | 0.2462 |
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+ | No log | 3.625 | 58 | 0.2492 | 0.1938 | 0.2494 |
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+ | No log | 3.75 | 60 | 0.2473 | 0.1556 | 0.2476 |
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+ | No log | 3.875 | 62 | 0.2559 | 0.1436 | 0.2563 |
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+ | No log | 4.0 | 64 | 0.2788 | 0.0972 | 0.2792 |
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+ | No log | 4.125 | 66 | 0.2859 | 0.0972 | 0.2863 |
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+ | No log | 4.25 | 68 | 0.2581 | 0.1146 | 0.2584 |
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+ | No log | 4.375 | 70 | 0.2414 | 0.1330 | 0.2417 |
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+ | No log | 4.5 | 72 | 0.2402 | 0.1344 | 0.2404 |
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+ | No log | 4.625 | 74 | 0.2406 | 0.1345 | 0.2408 |
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+ | No log | 4.75 | 76 | 0.2471 | 0.1446 | 0.2473 |
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+ | No log | 4.875 | 78 | 0.2567 | 0.1348 | 0.2570 |
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+ | No log | 5.0 | 80 | 0.2688 | 0.1201 | 0.2692 |
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+ | No log | 5.125 | 82 | 0.2619 | 0.1313 | 0.2622 |
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+ | No log | 5.25 | 84 | 0.2502 | 0.1611 | 0.2505 |
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+ | No log | 5.375 | 86 | 0.2499 | 0.1686 | 0.2501 |
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+ | No log | 5.5 | 88 | 0.2497 | 0.1609 | 0.2499 |
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+ | No log | 5.625 | 90 | 0.2590 | 0.1279 | 0.2592 |
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+ | No log | 5.75 | 92 | 0.2625 | 0.1201 | 0.2628 |
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+ | No log | 5.875 | 94 | 0.2585 | 0.1245 | 0.2588 |
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+ | No log | 6.0 | 96 | 0.2639 | 0.1100 | 0.2642 |
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+ | No log | 6.125 | 98 | 0.2653 | 0.1135 | 0.2656 |
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+ | No log | 6.25 | 100 | 0.2567 | 0.1199 | 0.2570 |
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+ | No log | 6.375 | 102 | 0.2499 | 0.1229 | 0.2502 |
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+ | No log | 6.5 | 104 | 0.2482 | 0.1311 | 0.2484 |
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+ | No log | 6.625 | 106 | 0.2482 | 0.1244 | 0.2485 |
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+ | No log | 6.75 | 108 | 0.2511 | 0.1210 | 0.2514 |
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+ | No log | 6.875 | 110 | 0.2518 | 0.1347 | 0.2521 |
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+ | No log | 7.0 | 112 | 0.2478 | 0.1381 | 0.2481 |
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+ | No log | 7.125 | 114 | 0.2465 | 0.1415 | 0.2468 |
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+ | No log | 7.25 | 116 | 0.2476 | 0.1379 | 0.2478 |
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+ | No log | 7.375 | 118 | 0.2505 | 0.1276 | 0.2508 |
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+ | No log | 7.5 | 120 | 0.2531 | 0.1381 | 0.2534 |
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+ | No log | 7.625 | 122 | 0.2620 | 0.1056 | 0.2623 |
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+ | No log | 7.75 | 124 | 0.2719 | 0.1180 | 0.2723 |
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+ | No log | 7.875 | 126 | 0.2767 | 0.1149 | 0.2770 |
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+ | No log | 8.0 | 128 | 0.2722 | 0.1095 | 0.2726 |
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+ | No log | 8.125 | 130 | 0.2637 | 0.1146 | 0.2640 |
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+ | No log | 8.25 | 132 | 0.2588 | 0.1178 | 0.2591 |
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+ | No log | 8.375 | 134 | 0.2564 | 0.1108 | 0.2567 |
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+ | No log | 8.5 | 136 | 0.2573 | 0.1042 | 0.2576 |
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+ | No log | 8.625 | 138 | 0.2581 | 0.0976 | 0.2584 |
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+ | No log | 8.75 | 140 | 0.2594 | 0.0976 | 0.2597 |
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+ | No log | 8.875 | 142 | 0.2629 | 0.0979 | 0.2632 |
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+ | No log | 9.0 | 144 | 0.2665 | 0.0946 | 0.2669 |
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+ | No log | 9.125 | 146 | 0.2676 | 0.0946 | 0.2679 |
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+ | No log | 9.25 | 148 | 0.2670 | 0.0946 | 0.2673 |
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+ | No log | 9.375 | 150 | 0.2667 | 0.0946 | 0.2671 |
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+ | No log | 9.5 | 152 | 0.2663 | 0.0979 | 0.2666 |
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+ | No log | 9.625 | 154 | 0.2661 | 0.0979 | 0.2664 |
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+ | No log | 9.75 | 156 | 0.2659 | 0.0979 | 0.2663 |
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+ | No log | 9.875 | 158 | 0.2661 | 0.1037 | 0.2664 |
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+ | No log | 10.0 | 160 | 0.2663 | 0.1037 | 0.2666 |
130
 
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  ### Framework versions
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