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arabert_cross_relevance_task2_fold4

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  1. README.md +83 -38
  2. model.safetensors +1 -1
  3. runs/Sep02_02-03-55_a09311c9b42d/events.out.tfevents.1725242637.a09311c9b42d.22.0 +3 -0
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  24. runs/Sep02_04-02-37_a09311c9b42d/events.out.tfevents.1725250511.a09311c9b42d.22.21 +3 -0
  25. runs/Sep02_04-15-12_a09311c9b42d/events.out.tfevents.1725250513.a09311c9b42d.22.22 +3 -0
  26. training_args.bin +1 -1
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_task2_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_task2_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: 0.2773
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- - Qwk: 0.2000
19
- - Mse: 0.2773
20
 
21
  ## Model description
22
 
@@ -36,47 +36,92 @@ 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
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: 1
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46
  ### Training results
47
 
48
  | Training Loss | Epoch | Step | Validation Loss | Qwk | Mse |
49
  |:-------------:|:------:|:----:|:---------------:|:------:|:------:|
50
- | No log | 0.0328 | 2 | 0.4959 | 0.0115 | 0.4959 |
51
- | No log | 0.0656 | 4 | 0.5590 | 0.0098 | 0.5590 |
52
- | No log | 0.0984 | 6 | 0.4608 | 0.0175 | 0.4608 |
53
- | No log | 0.1311 | 8 | 0.3699 | 0.1146 | 0.3699 |
54
- | No log | 0.1639 | 10 | 0.3890 | 0.1933 | 0.3890 |
55
- | No log | 0.1967 | 12 | 0.3716 | 0.1636 | 0.3716 |
56
- | No log | 0.2295 | 14 | 0.3268 | 0.1785 | 0.3268 |
57
- | No log | 0.2623 | 16 | 0.3074 | 0.1540 | 0.3074 |
58
- | No log | 0.2951 | 18 | 0.3082 | 0.1626 | 0.3082 |
59
- | No log | 0.3279 | 20 | 0.2888 | 0.2133 | 0.2888 |
60
- | No log | 0.3607 | 22 | 0.2650 | 0.2723 | 0.2650 |
61
- | No log | 0.3934 | 24 | 0.2579 | 0.3038 | 0.2579 |
62
- | No log | 0.4262 | 26 | 0.2636 | 0.2887 | 0.2636 |
63
- | No log | 0.4590 | 28 | 0.2743 | 0.2752 | 0.2743 |
64
- | No log | 0.4918 | 30 | 0.2965 | 0.2686 | 0.2965 |
65
- | No log | 0.5246 | 32 | 0.2942 | 0.2686 | 0.2942 |
66
- | No log | 0.5574 | 34 | 0.2803 | 0.2752 | 0.2803 |
67
- | No log | 0.5902 | 36 | 0.2689 | 0.2831 | 0.2689 |
68
- | No log | 0.6230 | 38 | 0.2660 | 0.2051 | 0.2660 |
69
- | No log | 0.6557 | 40 | 0.2706 | 0.1948 | 0.2706 |
70
- | No log | 0.6885 | 42 | 0.2746 | 0.1665 | 0.2746 |
71
- | No log | 0.7213 | 44 | 0.2765 | 0.1665 | 0.2765 |
72
- | No log | 0.7541 | 46 | 0.2792 | 0.1725 | 0.2792 |
73
- | No log | 0.7869 | 48 | 0.2798 | 0.1725 | 0.2798 |
74
- | No log | 0.8197 | 50 | 0.2802 | 0.1948 | 0.2802 |
75
- | No log | 0.8525 | 52 | 0.2797 | 0.2000 | 0.2797 |
76
- | No log | 0.8852 | 54 | 0.2802 | 0.2000 | 0.2802 |
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- | No log | 0.9180 | 56 | 0.2790 | 0.2000 | 0.2790 |
78
- | No log | 0.9508 | 58 | 0.2780 | 0.2000 | 0.2780 |
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- | No log | 0.9836 | 60 | 0.2773 | 0.2000 | 0.2773 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
80
 
81
 
82
  ### Framework versions
 
3
  tags:
4
  - generated_from_trainer
5
  model-index:
6
+ - name: arabert_cross_relevance_task2_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_task2_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: 0.2868
18
+ - Qwk: 0.4931
19
+ - Mse: 0.2868
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 | 0.1333 | 2 | 0.5163 | 0.2249 | 0.5163 |
51
+ | No log | 0.2667 | 4 | 0.4386 | 0.1958 | 0.4386 |
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+ | No log | 0.4 | 6 | 0.4172 | 0.1958 | 0.4172 |
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+ | No log | 0.5333 | 8 | 0.3488 | 0.2555 | 0.3488 |
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+ | No log | 0.6667 | 10 | 0.3483 | 0.2974 | 0.3483 |
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+ | No log | 0.8 | 12 | 0.3327 | 0.2718 | 0.3327 |
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+ | No log | 0.9333 | 14 | 0.3570 | 0.2289 | 0.3570 |
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+ | No log | 1.0667 | 16 | 0.3857 | 0.3184 | 0.3857 |
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+ | No log | 1.2 | 18 | 0.3553 | 0.2711 | 0.3553 |
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+ | No log | 1.3333 | 20 | 0.3072 | 0.2825 | 0.3072 |
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+ | No log | 1.4667 | 22 | 0.2870 | 0.3248 | 0.2870 |
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+ | No log | 1.6 | 24 | 0.2719 | 0.3375 | 0.2719 |
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+ | No log | 1.7333 | 26 | 0.2776 | 0.3974 | 0.2776 |
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+ | No log | 1.8667 | 28 | 0.2783 | 0.4688 | 0.2783 |
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+ | No log | 2.0 | 30 | 0.2844 | 0.5250 | 0.2844 |
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+ | No log | 2.1333 | 32 | 0.2948 | 0.5193 | 0.2948 |
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+ | No log | 2.2667 | 34 | 0.2802 | 0.375 | 0.2802 |
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+ | No log | 2.4 | 36 | 0.2657 | 0.3297 | 0.2657 |
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+ | No log | 2.5333 | 38 | 0.2635 | 0.3258 | 0.2635 |
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+ | No log | 2.6667 | 40 | 0.2700 | 0.3347 | 0.2700 |
70
+ | No log | 2.8 | 42 | 0.2862 | 0.3299 | 0.2862 |
71
+ | No log | 2.9333 | 44 | 0.3057 | 0.3666 | 0.3057 |
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+ | No log | 3.0667 | 46 | 0.3164 | 0.4048 | 0.3164 |
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+ | No log | 3.2 | 48 | 0.3074 | 0.3977 | 0.3074 |
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+ | No log | 3.3333 | 50 | 0.2918 | 0.3729 | 0.2918 |
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+ | No log | 3.4667 | 52 | 0.2907 | 0.4232 | 0.2907 |
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+ | No log | 3.6 | 54 | 0.2835 | 0.4066 | 0.2835 |
77
+ | No log | 3.7333 | 56 | 0.2768 | 0.3894 | 0.2768 |
78
+ | No log | 3.8667 | 58 | 0.2866 | 0.4187 | 0.2866 |
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+ | No log | 4.0 | 60 | 0.3010 | 0.4186 | 0.3010 |
80
+ | No log | 4.1333 | 62 | 0.3104 | 0.4066 | 0.3104 |
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+ | No log | 4.2667 | 64 | 0.2965 | 0.3773 | 0.2965 |
82
+ | No log | 4.4 | 66 | 0.2718 | 0.3398 | 0.2718 |
83
+ | No log | 4.5333 | 68 | 0.2585 | 0.3586 | 0.2585 |
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+ | No log | 4.6667 | 70 | 0.2610 | 0.3481 | 0.2610 |
85
+ | No log | 4.8 | 72 | 0.2741 | 0.3533 | 0.2741 |
86
+ | No log | 4.9333 | 74 | 0.2979 | 0.4156 | 0.2979 |
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+ | No log | 5.0667 | 76 | 0.3007 | 0.4214 | 0.3007 |
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+ | No log | 5.2 | 78 | 0.2959 | 0.3980 | 0.2959 |
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+ | No log | 5.3333 | 80 | 0.2864 | 0.3369 | 0.2864 |
90
+ | No log | 5.4667 | 82 | 0.2716 | 0.3458 | 0.2716 |
91
+ | No log | 5.6 | 84 | 0.2611 | 0.3307 | 0.2611 |
92
+ | No log | 5.7333 | 86 | 0.2596 | 0.3373 | 0.2596 |
93
+ | No log | 5.8667 | 88 | 0.2680 | 0.3583 | 0.2680 |
94
+ | No log | 6.0 | 90 | 0.2914 | 0.3969 | 0.2914 |
95
+ | No log | 6.1333 | 92 | 0.3171 | 0.4789 | 0.3171 |
96
+ | No log | 6.2667 | 94 | 0.3159 | 0.5187 | 0.3159 |
97
+ | No log | 6.4 | 96 | 0.3015 | 0.4948 | 0.3015 |
98
+ | No log | 6.5333 | 98 | 0.2857 | 0.4598 | 0.2857 |
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+ | No log | 6.6667 | 100 | 0.2723 | 0.4572 | 0.2723 |
100
+ | No log | 6.8 | 102 | 0.2683 | 0.4454 | 0.2683 |
101
+ | No log | 6.9333 | 104 | 0.2753 | 0.4473 | 0.2753 |
102
+ | No log | 7.0667 | 106 | 0.2829 | 0.4644 | 0.2829 |
103
+ | No log | 7.2 | 108 | 0.2793 | 0.4531 | 0.2793 |
104
+ | No log | 7.3333 | 110 | 0.2787 | 0.4531 | 0.2787 |
105
+ | No log | 7.4667 | 112 | 0.2754 | 0.4531 | 0.2754 |
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+ | No log | 7.6 | 114 | 0.2767 | 0.4600 | 0.2767 |
107
+ | No log | 7.7333 | 116 | 0.2854 | 0.4880 | 0.2854 |
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+ | No log | 7.8667 | 118 | 0.2920 | 0.5047 | 0.2920 |
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+ | No log | 8.0 | 120 | 0.2949 | 0.5212 | 0.2949 |
110
+ | No log | 8.1333 | 122 | 0.2935 | 0.5204 | 0.2935 |
111
+ | No log | 8.2667 | 124 | 0.2888 | 0.5040 | 0.2888 |
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+ | No log | 8.4 | 126 | 0.2843 | 0.4986 | 0.2843 |
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+ | No log | 8.5333 | 128 | 0.2811 | 0.5017 | 0.2811 |
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+ | No log | 8.6667 | 130 | 0.2800 | 0.5017 | 0.2800 |
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+ | No log | 8.8 | 132 | 0.2856 | 0.5125 | 0.2856 |
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+ | No log | 8.9333 | 134 | 0.2900 | 0.4986 | 0.2900 |
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+ | No log | 9.0667 | 136 | 0.2898 | 0.4986 | 0.2898 |
118
+ | No log | 9.2 | 138 | 0.2908 | 0.5040 | 0.2908 |
119
+ | No log | 9.3333 | 140 | 0.2914 | 0.5095 | 0.2914 |
120
+ | No log | 9.4667 | 142 | 0.2916 | 0.5047 | 0.2916 |
121
+ | No log | 9.6 | 144 | 0.2901 | 0.4986 | 0.2901 |
122
+ | No log | 9.7333 | 146 | 0.2879 | 0.4931 | 0.2879 |
123
+ | No log | 9.8667 | 148 | 0.2871 | 0.4931 | 0.2871 |
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+ | No log | 10.0 | 150 | 0.2868 | 0.4931 | 0.2868 |
125
 
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  ### Framework versions
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