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Training in progress, step 160

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  1. README.md +90 -40
  2. model.safetensors +1 -1
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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_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: 0.2645
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- - Qwk: 0.1072
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- - Mse: 0.2644
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21
  ## Model description
22
 
@@ -36,47 +36,97 @@ 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 |
49
- |:-------------:|:------:|:----:|:---------------:|:-------:|:------:|
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- | No log | 0.0328 | 2 | 0.4704 | 0.0057 | 0.4697 |
51
- | No log | 0.0656 | 4 | 0.3176 | -0.0223 | 0.3171 |
52
- | No log | 0.0984 | 6 | 0.2821 | 0.0390 | 0.2817 |
53
- | No log | 0.1311 | 8 | 0.3035 | 0.0686 | 0.3032 |
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- | No log | 0.1639 | 10 | 0.3619 | 0.0561 | 0.3616 |
55
- | No log | 0.1967 | 12 | 0.4061 | 0.0532 | 0.4058 |
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- | No log | 0.2295 | 14 | 0.3050 | 0.0584 | 0.3048 |
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- | No log | 0.2623 | 16 | 0.2732 | 0.0558 | 0.2730 |
58
- | No log | 0.2951 | 18 | 0.2742 | 0.0980 | 0.2741 |
59
- | No log | 0.3279 | 20 | 0.2913 | 0.1597 | 0.2912 |
60
- | No log | 0.3607 | 22 | 0.3074 | 0.1305 | 0.3073 |
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- | No log | 0.3934 | 24 | 0.3102 | 0.1122 | 0.3101 |
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- | No log | 0.4262 | 26 | 0.2890 | 0.1030 | 0.2889 |
63
- | No log | 0.4590 | 28 | 0.2757 | 0.1010 | 0.2756 |
64
- | No log | 0.4918 | 30 | 0.2754 | 0.1010 | 0.2753 |
65
- | No log | 0.5246 | 32 | 0.2810 | 0.0956 | 0.2809 |
66
- | No log | 0.5574 | 34 | 0.2873 | 0.0956 | 0.2871 |
67
- | No log | 0.5902 | 36 | 0.2867 | 0.1022 | 0.2865 |
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- | No log | 0.6230 | 38 | 0.2823 | 0.0965 | 0.2821 |
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- | No log | 0.6557 | 40 | 0.2783 | 0.0995 | 0.2782 |
70
- | No log | 0.6885 | 42 | 0.2789 | 0.1010 | 0.2788 |
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- | No log | 0.7213 | 44 | 0.2759 | 0.1049 | 0.2758 |
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- | No log | 0.7541 | 46 | 0.2725 | 0.1089 | 0.2724 |
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- | No log | 0.7869 | 48 | 0.2702 | 0.1036 | 0.2701 |
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- | No log | 0.8197 | 50 | 0.2660 | 0.0965 | 0.2659 |
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- | No log | 0.8525 | 52 | 0.2636 | 0.0849 | 0.2635 |
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- | No log | 0.8852 | 54 | 0.2636 | 0.0849 | 0.2635 |
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- | No log | 0.9180 | 56 | 0.2639 | 0.1072 | 0.2638 |
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- | No log | 0.9508 | 58 | 0.2645 | 0.1072 | 0.2644 |
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- | No log | 0.9836 | 60 | 0.2645 | 0.1072 | 0.2644 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
80
 
81
 
82
  ### Framework versions
 
3
  tags:
4
  - generated_from_trainer
5
  model-index:
6
+ - name: arabert_cross_relevance_task5_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_task5_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: 0.3006
18
+ - Qwk: 0.2137
19
+ - Mse: 0.3007
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 | 1.0217 | 0.0195 | 1.0225 |
51
+ | No log | 0.25 | 4 | 0.4152 | 0.0535 | 0.4143 |
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+ | No log | 0.375 | 6 | 0.3599 | 0.0454 | 0.3596 |
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+ | No log | 0.5 | 8 | 0.3055 | 0.0426 | 0.3056 |
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+ | No log | 0.625 | 10 | 0.2854 | 0.0805 | 0.2861 |
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+ | No log | 0.75 | 12 | 0.2641 | 0.1393 | 0.2644 |
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+ | No log | 0.875 | 14 | 0.2524 | 0.1301 | 0.2527 |
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+ | No log | 1.0 | 16 | 0.2428 | 0.1915 | 0.2430 |
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+ | No log | 1.125 | 18 | 0.2426 | 0.1915 | 0.2428 |
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+ | No log | 1.25 | 20 | 0.2443 | 0.1915 | 0.2447 |
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+ | No log | 1.375 | 22 | 0.2471 | 0.1854 | 0.2474 |
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+ | No log | 1.5 | 24 | 0.2514 | 0.1890 | 0.2517 |
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+ | No log | 1.625 | 26 | 0.2516 | 0.1638 | 0.2519 |
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+ | No log | 1.75 | 28 | 0.2545 | 0.1467 | 0.2547 |
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+ | No log | 1.875 | 30 | 0.2544 | 0.1816 | 0.2547 |
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+ | No log | 2.0 | 32 | 0.2492 | 0.2200 | 0.2495 |
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+ | No log | 2.125 | 34 | 0.2568 | 0.2044 | 0.2572 |
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+ | No log | 2.25 | 36 | 0.2853 | 0.2266 | 0.2857 |
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+ | No log | 2.375 | 38 | 0.2827 | 0.2137 | 0.2831 |
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+ | No log | 2.5 | 40 | 0.2560 | 0.2018 | 0.2565 |
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+ | No log | 2.625 | 42 | 0.2538 | 0.2177 | 0.2543 |
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+ | No log | 2.75 | 44 | 0.2538 | 0.1854 | 0.2542 |
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+ | No log | 2.875 | 46 | 0.2581 | 0.2064 | 0.2584 |
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+ | No log | 3.0 | 48 | 0.2645 | 0.2064 | 0.2648 |
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+ | No log | 3.125 | 50 | 0.2629 | 0.1830 | 0.2631 |
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+ | No log | 3.25 | 52 | 0.2615 | 0.1539 | 0.2618 |
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+ | No log | 3.375 | 54 | 0.2644 | 0.1588 | 0.2646 |
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+ | No log | 3.5 | 56 | 0.2734 | 0.2119 | 0.2736 |
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+ | No log | 3.625 | 58 | 0.2799 | 0.2050 | 0.2801 |
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+ | No log | 3.75 | 60 | 0.2702 | 0.2050 | 0.2704 |
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+ | No log | 3.875 | 62 | 0.2549 | 0.1999 | 0.2553 |
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+ | No log | 4.0 | 64 | 0.2524 | 0.2274 | 0.2528 |
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+ | No log | 4.125 | 66 | 0.2506 | 0.2274 | 0.2510 |
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+ | No log | 4.25 | 68 | 0.2560 | 0.1999 | 0.2563 |
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+ | No log | 4.375 | 70 | 0.2850 | 0.2194 | 0.2853 |
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+ | No log | 4.5 | 72 | 0.3006 | 0.2282 | 0.3008 |
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+ | No log | 4.625 | 74 | 0.2929 | 0.2099 | 0.2931 |
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+ | No log | 4.75 | 76 | 0.2761 | 0.2109 | 0.2764 |
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+ | No log | 4.875 | 78 | 0.2669 | 0.2119 | 0.2671 |
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+ | No log | 5.0 | 80 | 0.2664 | 0.2057 | 0.2667 |
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+ | No log | 5.125 | 82 | 0.2687 | 0.2109 | 0.2689 |
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+ | No log | 5.25 | 84 | 0.2617 | 0.2109 | 0.2619 |
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+ | No log | 5.375 | 86 | 0.2588 | 0.2109 | 0.2590 |
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+ | No log | 5.5 | 88 | 0.2627 | 0.2050 | 0.2628 |
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+ | No log | 5.625 | 90 | 0.2860 | 0.2147 | 0.2861 |
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+ | No log | 5.75 | 92 | 0.3309 | 0.2252 | 0.3309 |
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+ | No log | 5.875 | 94 | 0.3340 | 0.2200 | 0.3341 |
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+ | No log | 6.0 | 96 | 0.3021 | 0.2083 | 0.3022 |
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+ | No log | 6.125 | 98 | 0.2691 | 0.2173 | 0.2694 |
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+ | No log | 6.25 | 100 | 0.2601 | 0.2200 | 0.2604 |
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+ | No log | 6.375 | 102 | 0.2632 | 0.2173 | 0.2635 |
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+ | No log | 6.5 | 104 | 0.2738 | 0.2220 | 0.2741 |
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+ | No log | 6.625 | 106 | 0.2881 | 0.2250 | 0.2884 |
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+ | No log | 6.75 | 108 | 0.3079 | 0.2127 | 0.3081 |
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+ | No log | 6.875 | 110 | 0.3154 | 0.2170 | 0.3156 |
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+ | No log | 7.0 | 112 | 0.3054 | 0.2137 | 0.3056 |
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+ | No log | 7.125 | 114 | 0.2897 | 0.2091 | 0.2899 |
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+ | No log | 7.25 | 116 | 0.2842 | 0.2044 | 0.2844 |
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+ | No log | 7.375 | 118 | 0.2794 | 0.2099 | 0.2796 |
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+ | No log | 7.5 | 120 | 0.2789 | 0.2099 | 0.2791 |
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+ | No log | 7.625 | 122 | 0.2813 | 0.2099 | 0.2814 |
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+ | No log | 7.75 | 124 | 0.2926 | 0.2091 | 0.2927 |
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+ | No log | 7.875 | 126 | 0.3068 | 0.2137 | 0.3069 |
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+ | No log | 8.0 | 128 | 0.3323 | 0.2118 | 0.3323 |
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+ | No log | 8.125 | 130 | 0.3463 | 0.2070 | 0.3463 |
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+ | No log | 8.25 | 132 | 0.3382 | 0.2118 | 0.3383 |
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+ | No log | 8.375 | 134 | 0.3313 | 0.2118 | 0.3314 |
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+ | No log | 8.5 | 136 | 0.3174 | 0.2137 | 0.3174 |
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+ | No log | 8.625 | 138 | 0.3049 | 0.2137 | 0.3050 |
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+ | No log | 8.75 | 140 | 0.3007 | 0.2137 | 0.3008 |
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+ | No log | 8.875 | 142 | 0.2970 | 0.2137 | 0.2971 |
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+ | No log | 9.0 | 144 | 0.2949 | 0.2137 | 0.2950 |
122
+ | No log | 9.125 | 146 | 0.2966 | 0.2137 | 0.2967 |
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+ | No log | 9.25 | 148 | 0.2992 | 0.2137 | 0.2994 |
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+ | No log | 9.375 | 150 | 0.2997 | 0.2137 | 0.2999 |
125
+ | No log | 9.5 | 152 | 0.3018 | 0.2137 | 0.3019 |
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+ | No log | 9.625 | 154 | 0.3012 | 0.2137 | 0.3013 |
127
+ | No log | 9.75 | 156 | 0.3004 | 0.2137 | 0.3006 |
128
+ | No log | 9.875 | 158 | 0.3005 | 0.2137 | 0.3006 |
129
+ | No log | 10.0 | 160 | 0.3006 | 0.2137 | 0.3007 |
130
 
131
 
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  ### Framework versions
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