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arabert_cross_vocabulary_task1_fold0

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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_vocabulary_task1_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_vocabulary_task1_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: 0.9107
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- - Qwk: 0.3160
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- - Mse: 0.9107
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  ## Model description
22
 
@@ -36,45 +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
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  - 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
47
 
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- | Training Loss | Epoch | Step | Validation Loss | Qwk | Mse |
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- |:-------------:|:------:|:----:|:---------------:|:------:|:------:|
50
- | No log | 0.0351 | 2 | 3.6812 | 0.0124 | 3.6812 |
51
- | No log | 0.0702 | 4 | 2.2449 | 0.0807 | 2.2449 |
52
- | No log | 0.1053 | 6 | 1.7920 | 0.1291 | 1.7920 |
53
- | No log | 0.1404 | 8 | 1.1077 | 0.2184 | 1.1077 |
54
- | No log | 0.1754 | 10 | 1.6727 | 0.2157 | 1.6727 |
55
- | No log | 0.2105 | 12 | 2.3411 | 0.1852 | 2.3411 |
56
- | No log | 0.2456 | 14 | 1.4252 | 0.2951 | 1.4252 |
57
- | No log | 0.2807 | 16 | 0.8885 | 0.3981 | 0.8885 |
58
- | No log | 0.3158 | 18 | 0.6824 | 0.4387 | 0.6824 |
59
- | No log | 0.3509 | 20 | 0.6604 | 0.4473 | 0.6604 |
60
- | No log | 0.3860 | 22 | 0.7208 | 0.3880 | 0.7208 |
61
- | No log | 0.4211 | 24 | 1.1639 | 0.2846 | 1.1639 |
62
- | No log | 0.4561 | 26 | 2.0330 | 0.1689 | 2.0330 |
63
- | No log | 0.4912 | 28 | 2.2500 | 0.1485 | 2.2500 |
64
- | No log | 0.5263 | 30 | 1.8145 | 0.1758 | 1.8145 |
65
- | No log | 0.5614 | 32 | 1.1982 | 0.2547 | 1.1982 |
66
- | No log | 0.5965 | 34 | 0.8111 | 0.3192 | 0.8111 |
67
- | No log | 0.6316 | 36 | 0.7359 | 0.3443 | 0.7359 |
68
- | No log | 0.6667 | 38 | 0.8012 | 0.3164 | 0.8012 |
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- | No log | 0.7018 | 40 | 0.9036 | 0.2985 | 0.9036 |
70
- | No log | 0.7368 | 42 | 1.0075 | 0.2804 | 1.0075 |
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- | No log | 0.7719 | 44 | 1.0761 | 0.2855 | 1.0761 |
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- | No log | 0.8070 | 46 | 1.0400 | 0.2883 | 1.0400 |
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- | No log | 0.8421 | 48 | 1.0379 | 0.2963 | 1.0379 |
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- | No log | 0.8772 | 50 | 1.0163 | 0.3002 | 1.0163 |
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- | No log | 0.9123 | 52 | 0.9760 | 0.3168 | 0.9760 |
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- | No log | 0.9474 | 54 | 0.9286 | 0.3206 | 0.9286 |
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- | No log | 0.9825 | 56 | 0.9107 | 0.3160 | 0.9107 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
78
 
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  ### Framework versions
 
3
  tags:
4
  - generated_from_trainer
5
  model-index:
6
+ - name: arabert_cross_relevance_task7_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_task7_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: 0.4397
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+ - Qwk: 0.1488
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+ - Mse: 0.4393
20
 
21
  ## Model description
22
 
 
36
 
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  The following hyperparameters were used during training:
38
  - learning_rate: 2e-05
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+ - train_batch_size: 64
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+ - eval_batch_size: 64
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  - seed: 42
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  - 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: 10
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46
  ### Training results
47
 
48
+ | Training Loss | Epoch | Step | Validation Loss | Qwk | Mse |
49
+ |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
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+ | No log | 0.125 | 2 | 0.7246 | 0.0092 | 0.7226 |
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+ | No log | 0.25 | 4 | 0.3923 | 0.1169 | 0.3915 |
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+ | No log | 0.375 | 6 | 0.3543 | 0.0420 | 0.3537 |
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+ | No log | 0.5 | 8 | 0.3794 | 0.1151 | 0.3788 |
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+ | No log | 0.625 | 10 | 0.3085 | 0.0822 | 0.3084 |
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+ | No log | 0.75 | 12 | 0.2791 | 0.0429 | 0.2796 |
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+ | No log | 0.875 | 14 | 0.2793 | 0.0732 | 0.2799 |
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+ | No log | 1.0 | 16 | 0.2798 | 0.0822 | 0.2804 |
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+ | No log | 1.125 | 18 | 0.2748 | 0.1450 | 0.2754 |
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+ | No log | 1.25 | 20 | 0.2618 | 0.1769 | 0.2623 |
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+ | No log | 1.375 | 22 | 0.2610 | 0.2119 | 0.2614 |
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+ | No log | 1.5 | 24 | 0.2714 | 0.2099 | 0.2716 |
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+ | No log | 1.625 | 26 | 0.2877 | 0.2282 | 0.2877 |
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+ | No log | 1.75 | 28 | 0.3085 | 0.2170 | 0.3085 |
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+ | No log | 1.875 | 30 | 0.2818 | 0.2521 | 0.2819 |
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+ | No log | 2.0 | 32 | 0.2704 | 0.2285 | 0.2706 |
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+ | No log | 2.125 | 34 | 0.2630 | 0.2177 | 0.2635 |
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+ | No log | 2.25 | 36 | 0.2577 | 0.1930 | 0.2582 |
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+ | No log | 2.375 | 38 | 0.2575 | 0.2186 | 0.2579 |
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+ | No log | 2.5 | 40 | 0.2613 | 0.2282 | 0.2617 |
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+ | No log | 2.625 | 42 | 0.2766 | 0.2044 | 0.2769 |
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+ | No log | 2.75 | 44 | 0.2809 | 0.2091 | 0.2811 |
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+ | No log | 2.875 | 46 | 0.2689 | 0.2194 | 0.2691 |
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+ | No log | 3.0 | 48 | 0.2629 | 0.2198 | 0.2632 |
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+ | No log | 3.125 | 50 | 0.2671 | 0.2133 | 0.2672 |
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+ | No log | 3.25 | 52 | 0.2896 | 0.2170 | 0.2895 |
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+ | No log | 3.375 | 54 | 0.3099 | 0.2118 | 0.3097 |
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+ | No log | 3.5 | 56 | 0.2867 | 0.2181 | 0.2867 |
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+ | No log | 3.625 | 58 | 0.2681 | 0.2108 | 0.2683 |
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+ | No log | 3.75 | 60 | 0.2670 | 0.2042 | 0.2674 |
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+ | No log | 3.875 | 62 | 0.2777 | 0.2220 | 0.2780 |
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+ | No log | 4.0 | 64 | 0.2823 | 0.2220 | 0.2826 |
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+ | No log | 4.125 | 66 | 0.2925 | 0.2150 | 0.2927 |
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+ | No log | 4.25 | 68 | 0.3165 | 0.2285 | 0.3164 |
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+ | No log | 4.375 | 70 | 0.3340 | 0.2156 | 0.3337 |
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+ | No log | 4.5 | 72 | 0.3690 | 0.1876 | 0.3685 |
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+ | No log | 4.625 | 74 | 0.3812 | 0.1800 | 0.3806 |
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+ | No log | 4.75 | 76 | 0.3599 | 0.1954 | 0.3594 |
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+ | No log | 4.875 | 78 | 0.3297 | 0.2097 | 0.3294 |
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+ | No log | 5.0 | 80 | 0.3082 | 0.2063 | 0.3081 |
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+ | No log | 5.125 | 82 | 0.2990 | 0.2193 | 0.2991 |
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+ | No log | 5.25 | 84 | 0.3004 | 0.2193 | 0.3005 |
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+ | No log | 5.375 | 86 | 0.3010 | 0.2140 | 0.3011 |
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+ | No log | 5.5 | 88 | 0.3297 | 0.1814 | 0.3298 |
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+ | No log | 5.625 | 90 | 0.3943 | 0.1785 | 0.3943 |
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+ | No log | 5.75 | 92 | 0.4229 | 0.1592 | 0.4228 |
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+ | No log | 5.875 | 94 | 0.3892 | 0.1719 | 0.3892 |
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+ | No log | 6.0 | 96 | 0.3418 | 0.1836 | 0.3418 |
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+ | No log | 6.125 | 98 | 0.3361 | 0.1932 | 0.3360 |
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+ | No log | 6.25 | 100 | 0.3641 | 0.1930 | 0.3638 |
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+ | No log | 6.375 | 102 | 0.3934 | 0.1844 | 0.3930 |
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+ | No log | 6.5 | 104 | 0.3956 | 0.1915 | 0.3953 |
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+ | No log | 6.625 | 106 | 0.3700 | 0.2006 | 0.3700 |
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+ | No log | 6.75 | 108 | 0.3683 | 0.1800 | 0.3684 |
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+ | No log | 6.875 | 110 | 0.3757 | 0.1785 | 0.3758 |
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+ | No log | 7.0 | 112 | 0.4066 | 0.1688 | 0.4066 |
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+ | No log | 7.125 | 114 | 0.4152 | 0.1695 | 0.4151 |
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+ | No log | 7.25 | 116 | 0.3917 | 0.1790 | 0.3917 |
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+ | No log | 7.375 | 118 | 0.3540 | 0.1833 | 0.3542 |
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+ | No log | 7.5 | 120 | 0.3449 | 0.1998 | 0.3451 |
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+ | No log | 7.625 | 122 | 0.3587 | 0.1955 | 0.3588 |
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+ | No log | 7.75 | 124 | 0.3969 | 0.1807 | 0.3968 |
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+ | No log | 7.875 | 126 | 0.4580 | 0.1405 | 0.4577 |
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+ | No log | 8.0 | 128 | 0.5018 | 0.1433 | 0.5013 |
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+ | No log | 8.125 | 130 | 0.5002 | 0.1433 | 0.4997 |
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+ | No log | 8.25 | 132 | 0.4689 | 0.1442 | 0.4684 |
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+ | No log | 8.375 | 134 | 0.4386 | 0.1488 | 0.4382 |
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+ | No log | 8.5 | 136 | 0.4174 | 0.1550 | 0.4171 |
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+ | No log | 8.625 | 138 | 0.4152 | 0.1613 | 0.4149 |
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+ | No log | 8.75 | 140 | 0.4293 | 0.1550 | 0.4290 |
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+ | No log | 8.875 | 142 | 0.4512 | 0.1427 | 0.4508 |
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+ | No log | 9.0 | 144 | 0.4641 | 0.1405 | 0.4637 |
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+ | No log | 9.125 | 146 | 0.4566 | 0.1427 | 0.4562 |
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+ | No log | 9.25 | 148 | 0.4432 | 0.1427 | 0.4429 |
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+ | No log | 9.375 | 150 | 0.4330 | 0.1550 | 0.4327 |
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+ | No log | 9.5 | 152 | 0.4301 | 0.1613 | 0.4298 |
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+ | No log | 9.625 | 154 | 0.4343 | 0.1550 | 0.4340 |
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+ | No log | 9.75 | 156 | 0.4358 | 0.1550 | 0.4354 |
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+ | No log | 9.875 | 158 | 0.4385 | 0.1488 | 0.4381 |
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+ | No log | 10.0 | 160 | 0.4397 | 0.1488 | 0.4393 |
130
 
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  ### Framework versions
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