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arabert_cross_relevance_task4_fold4

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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_task4_fold4
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_fold4
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: 0.2131
18
- - Qwk: 0.2800
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- - Mse: 0.2131
20
 
21
  ## Model description
22
 
@@ -36,51 +36,102 @@ More information needed
36
 
37
  The following hyperparameters were used during training:
38
  - 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
45
 
46
  ### Training results
47
 
48
  | Training Loss | Epoch | Step | Validation Loss | Qwk | Mse |
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  |:-------------:|:------:|:----:|:---------------:|:------:|:------:|
50
- | No log | 0.0290 | 2 | 1.5877 | 0.0071 | 1.5877 |
51
- | No log | 0.0580 | 4 | 0.7523 | 0.0797 | 0.7523 |
52
- | No log | 0.0870 | 6 | 0.4972 | 0.2325 | 0.4972 |
53
- | No log | 0.1159 | 8 | 0.4973 | 0.2818 | 0.4973 |
54
- | No log | 0.1449 | 10 | 0.3782 | 0.2548 | 0.3782 |
55
- | No log | 0.1739 | 12 | 0.3328 | 0.2641 | 0.3328 |
56
- | No log | 0.2029 | 14 | 0.2810 | 0.2677 | 0.2810 |
57
- | No log | 0.2319 | 16 | 0.2749 | 0.2717 | 0.2749 |
58
- | No log | 0.2609 | 18 | 0.2745 | 0.2169 | 0.2745 |
59
- | No log | 0.2899 | 20 | 0.2605 | 0.2602 | 0.2605 |
60
- | No log | 0.3188 | 22 | 0.2453 | 0.2528 | 0.2453 |
61
- | No log | 0.3478 | 24 | 0.2442 | 0.2459 | 0.2442 |
62
- | No log | 0.3768 | 26 | 0.2468 | 0.2763 | 0.2468 |
63
- | No log | 0.4058 | 28 | 0.2595 | 0.2864 | 0.2595 |
64
- | No log | 0.4348 | 30 | 0.2694 | 0.2852 | 0.2694 |
65
- | No log | 0.4638 | 32 | 0.2515 | 0.2790 | 0.2515 |
66
- | No log | 0.4928 | 34 | 0.2280 | 0.3189 | 0.2280 |
67
- | No log | 0.5217 | 36 | 0.2522 | 0.4255 | 0.2522 |
68
- | No log | 0.5507 | 38 | 0.2616 | 0.3794 | 0.2616 |
69
- | No log | 0.5797 | 40 | 0.2487 | 0.2990 | 0.2487 |
70
- | No log | 0.6087 | 42 | 0.2345 | 0.2490 | 0.2345 |
71
- | No log | 0.6377 | 44 | 0.2296 | 0.2615 | 0.2296 |
72
- | No log | 0.6667 | 46 | 0.2262 | 0.2654 | 0.2262 |
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- | No log | 0.6957 | 48 | 0.2230 | 0.2654 | 0.2230 |
74
- | No log | 0.7246 | 50 | 0.2198 | 0.2691 | 0.2198 |
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- | No log | 0.7536 | 52 | 0.2182 | 0.2728 | 0.2182 |
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- | No log | 0.7826 | 54 | 0.2166 | 0.2763 | 0.2166 |
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- | No log | 0.8116 | 56 | 0.2162 | 0.2763 | 0.2162 |
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- | No log | 0.8406 | 58 | 0.2158 | 0.2798 | 0.2158 |
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- | No log | 0.8696 | 60 | 0.2144 | 0.2798 | 0.2144 |
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- | No log | 0.8986 | 62 | 0.2129 | 0.2798 | 0.2129 |
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- | No log | 0.9275 | 64 | 0.2125 | 0.2763 | 0.2125 |
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- | No log | 0.9565 | 66 | 0.2128 | 0.2728 | 0.2128 |
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- | No log | 0.9855 | 68 | 0.2131 | 0.2800 | 0.2131 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
84
 
85
 
86
  ### Framework versions
 
3
  tags:
4
  - generated_from_trainer
5
  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:
17
+ - Loss: 0.3037
18
+ - Qwk: 0.3732
19
+ - Mse: 0.3037
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 | 0.1176 | 2 | 0.5630 | 0.1562 | 0.5630 |
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+ | No log | 0.2353 | 4 | 0.4644 | 0.2174 | 0.4644 |
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+ | No log | 0.3529 | 6 | 0.3950 | 0.1962 | 0.3950 |
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+ | No log | 0.4706 | 8 | 0.3834 | 0.2684 | 0.3834 |
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+ | No log | 0.5882 | 10 | 0.3306 | 0.3081 | 0.3306 |
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+ | No log | 0.7059 | 12 | 0.3268 | 0.2811 | 0.3268 |
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+ | No log | 0.8235 | 14 | 0.3154 | 0.3011 | 0.3154 |
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+ | No log | 0.9412 | 16 | 0.3060 | 0.3218 | 0.3060 |
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+ | No log | 1.0588 | 18 | 0.3117 | 0.3651 | 0.3117 |
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+ | No log | 1.1765 | 20 | 0.3057 | 0.3773 | 0.3057 |
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+ | No log | 1.2941 | 22 | 0.3034 | 0.3911 | 0.3034 |
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+ | No log | 1.4118 | 24 | 0.2791 | 0.4002 | 0.2791 |
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+ | No log | 1.5294 | 26 | 0.2627 | 0.4023 | 0.2627 |
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+ | No log | 1.6471 | 28 | 0.2813 | 0.3853 | 0.2813 |
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+ | No log | 1.7647 | 30 | 0.3082 | 0.3740 | 0.3082 |
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+ | No log | 1.8824 | 32 | 0.2928 | 0.3614 | 0.2928 |
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+ | No log | 2.0 | 34 | 0.2792 | 0.3430 | 0.2792 |
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+ | No log | 2.1176 | 36 | 0.2640 | 0.3836 | 0.2640 |
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+ | No log | 2.2353 | 38 | 0.2797 | 0.4090 | 0.2797 |
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+ | No log | 2.3529 | 40 | 0.3047 | 0.3991 | 0.3047 |
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+ | No log | 2.4706 | 42 | 0.3233 | 0.3483 | 0.3233 |
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+ | No log | 2.5882 | 44 | 0.3173 | 0.3975 | 0.3173 |
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+ | No log | 2.7059 | 46 | 0.2794 | 0.3702 | 0.2794 |
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+ | No log | 2.8235 | 48 | 0.2545 | 0.3595 | 0.2545 |
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+ | No log | 2.9412 | 50 | 0.2598 | 0.3274 | 0.2598 |
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+ | No log | 3.0588 | 52 | 0.3170 | 0.2780 | 0.3170 |
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+ | No log | 3.1765 | 54 | 0.3616 | 0.2701 | 0.3616 |
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+ | No log | 3.2941 | 56 | 0.3399 | 0.3799 | 0.3399 |
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+ | No log | 3.4118 | 58 | 0.2912 | 0.4991 | 0.2912 |
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+ | No log | 3.5294 | 60 | 0.2788 | 0.5808 | 0.2788 |
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+ | No log | 3.6471 | 62 | 0.2781 | 0.5944 | 0.2781 |
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+ | No log | 3.7647 | 64 | 0.2655 | 0.5547 | 0.2655 |
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+ | No log | 3.8824 | 66 | 0.2739 | 0.4479 | 0.2739 |
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+ | No log | 4.0 | 68 | 0.3052 | 0.3580 | 0.3052 |
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+ | No log | 4.1176 | 70 | 0.3257 | 0.2703 | 0.3257 |
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+ | No log | 4.2353 | 72 | 0.3077 | 0.2765 | 0.3077 |
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+ | No log | 4.3529 | 74 | 0.2673 | 0.3446 | 0.2673 |
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+ | No log | 4.4706 | 76 | 0.2558 | 0.4205 | 0.2558 |
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+ | No log | 4.5882 | 78 | 0.2699 | 0.4751 | 0.2699 |
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+ | No log | 4.7059 | 80 | 0.3058 | 0.5205 | 0.3058 |
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+ | No log | 4.8235 | 82 | 0.3248 | 0.5030 | 0.3248 |
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+ | No log | 4.9412 | 84 | 0.3083 | 0.4300 | 0.3083 |
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+ | No log | 5.0588 | 86 | 0.2844 | 0.3512 | 0.2844 |
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+ | No log | 5.1765 | 88 | 0.2595 | 0.3405 | 0.2595 |
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+ | No log | 5.2941 | 90 | 0.2544 | 0.3462 | 0.2544 |
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+ | No log | 5.4118 | 92 | 0.2686 | 0.3378 | 0.2686 |
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+ | No log | 5.5294 | 94 | 0.3037 | 0.3446 | 0.3037 |
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+ | No log | 5.6471 | 96 | 0.3453 | 0.3453 | 0.3453 |
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+ | No log | 5.7647 | 98 | 0.3438 | 0.3956 | 0.3438 |
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+ | No log | 5.8824 | 100 | 0.3084 | 0.4184 | 0.3084 |
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+ | No log | 6.0 | 102 | 0.2757 | 0.4015 | 0.2757 |
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+ | No log | 6.1176 | 104 | 0.2744 | 0.3963 | 0.2744 |
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+ | No log | 6.2353 | 106 | 0.2900 | 0.4343 | 0.2900 |
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+ | No log | 6.3529 | 108 | 0.3167 | 0.4357 | 0.3167 |
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+ | No log | 6.4706 | 110 | 0.3249 | 0.4225 | 0.3249 |
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+ | No log | 6.5882 | 112 | 0.3104 | 0.3929 | 0.3104 |
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+ | No log | 6.7059 | 114 | 0.2965 | 0.3961 | 0.2965 |
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+ | No log | 6.8235 | 116 | 0.2870 | 0.3956 | 0.2870 |
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+ | No log | 6.9412 | 118 | 0.2835 | 0.4017 | 0.2835 |
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+ | No log | 7.0588 | 120 | 0.2798 | 0.4117 | 0.2798 |
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+ | No log | 7.1765 | 122 | 0.2952 | 0.3838 | 0.2952 |
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+ | No log | 7.2941 | 124 | 0.3094 | 0.3838 | 0.3094 |
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+ | No log | 7.4118 | 126 | 0.3254 | 0.4226 | 0.3254 |
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+ | No log | 7.5294 | 128 | 0.3223 | 0.4122 | 0.3223 |
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+ | No log | 7.6471 | 130 | 0.3091 | 0.3910 | 0.3091 |
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+ | No log | 7.7647 | 132 | 0.3042 | 0.3896 | 0.3042 |
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+ | No log | 7.8824 | 134 | 0.2977 | 0.3822 | 0.2977 |
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+ | No log | 8.0 | 136 | 0.2987 | 0.3536 | 0.2987 |
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+ | No log | 8.1176 | 138 | 0.3110 | 0.3437 | 0.3110 |
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+ | No log | 8.2353 | 140 | 0.3121 | 0.3392 | 0.3121 |
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+ | No log | 8.3529 | 142 | 0.3056 | 0.3402 | 0.3056 |
121
+ | No log | 8.4706 | 144 | 0.3047 | 0.3462 | 0.3047 |
122
+ | No log | 8.5882 | 146 | 0.3035 | 0.3572 | 0.3035 |
123
+ | No log | 8.7059 | 148 | 0.3024 | 0.3690 | 0.3024 |
124
+ | No log | 8.8235 | 150 | 0.3034 | 0.3717 | 0.3034 |
125
+ | No log | 8.9412 | 152 | 0.3012 | 0.3774 | 0.3012 |
126
+ | No log | 9.0588 | 154 | 0.2988 | 0.3774 | 0.2988 |
127
+ | No log | 9.1765 | 156 | 0.3009 | 0.3774 | 0.3009 |
128
+ | No log | 9.2941 | 158 | 0.3001 | 0.3889 | 0.3001 |
129
+ | No log | 9.4118 | 160 | 0.3015 | 0.3946 | 0.3015 |
130
+ | No log | 9.5294 | 162 | 0.3032 | 0.3946 | 0.3032 |
131
+ | No log | 9.6471 | 164 | 0.3050 | 0.3846 | 0.3050 |
132
+ | No log | 9.7647 | 166 | 0.3044 | 0.3732 | 0.3044 |
133
+ | No log | 9.8824 | 168 | 0.3039 | 0.3732 | 0.3039 |
134
+ | No log | 10.0 | 170 | 0.3037 | 0.3732 | 0.3037 |
135
 
136
 
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  ### Framework versions
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