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  1. README.md +85 -41
  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_task7_fold2
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_fold2
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: 0.3216
18
- - Qwk: 0.0122
19
- - Mse: 0.3221
20
 
21
  ## Model description
22
 
@@ -36,48 +36,92 @@ 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
43
  - 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 |
49
- |:-------------:|:------:|:----:|:---------------:|:-------:|:------:|
50
- | No log | 0.0317 | 2 | 0.3702 | 0.0004 | 0.3710 |
51
- | No log | 0.0635 | 4 | 0.6663 | 0.0876 | 0.6665 |
52
- | No log | 0.0952 | 6 | 0.4892 | -0.0369 | 0.4902 |
53
- | No log | 0.1270 | 8 | 0.3495 | 0.0201 | 0.3512 |
54
- | No log | 0.1587 | 10 | 0.3025 | 0.0245 | 0.3043 |
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- | No log | 0.1905 | 12 | 0.2923 | 0.0122 | 0.2940 |
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- | No log | 0.2222 | 14 | 0.3016 | 0.0 | 0.3031 |
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- | No log | 0.2540 | 16 | 0.3279 | 0.0203 | 0.3288 |
58
- | No log | 0.2857 | 18 | 0.3285 | 0.0080 | 0.3293 |
59
- | No log | 0.3175 | 20 | 0.3021 | 0.0122 | 0.3033 |
60
- | No log | 0.3492 | 22 | 0.3021 | 0.0 | 0.3033 |
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- | No log | 0.3810 | 24 | 0.3213 | -0.0005 | 0.3221 |
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- | No log | 0.4127 | 26 | 0.3319 | 0.0368 | 0.3326 |
63
- | No log | 0.4444 | 28 | 0.3452 | 0.0619 | 0.3456 |
64
- | No log | 0.4762 | 30 | 0.3248 | 0.0534 | 0.3253 |
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- | No log | 0.5079 | 32 | 0.3076 | 0.0080 | 0.3082 |
66
- | No log | 0.5397 | 34 | 0.2862 | 0.0 | 0.2870 |
67
- | No log | 0.5714 | 36 | 0.2769 | 0.0 | 0.2777 |
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- | No log | 0.6032 | 38 | 0.2750 | 0.0 | 0.2759 |
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- | No log | 0.6349 | 40 | 0.2747 | 0.0 | 0.2756 |
70
- | No log | 0.6667 | 42 | 0.2748 | 0.0 | 0.2756 |
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- | No log | 0.6984 | 44 | 0.2760 | 0.0 | 0.2767 |
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- | No log | 0.7302 | 46 | 0.2797 | 0.0 | 0.2803 |
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- | No log | 0.7619 | 48 | 0.2898 | 0.0 | 0.2903 |
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- | No log | 0.7937 | 50 | 0.2997 | 0.0 | 0.3002 |
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- | No log | 0.8254 | 52 | 0.3072 | 0.0 | 0.3077 |
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- | No log | 0.8571 | 54 | 0.3115 | 0.0 | 0.3120 |
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- | No log | 0.8889 | 56 | 0.3144 | 0.0 | 0.3148 |
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- | No log | 0.9206 | 58 | 0.3154 | 0.0122 | 0.3159 |
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- | No log | 0.9524 | 60 | 0.3184 | 0.0122 | 0.3189 |
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- | No log | 0.9841 | 62 | 0.3216 | 0.0122 | 0.3221 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
81
 
82
 
83
  ### Framework versions
 
3
  tags:
4
  - generated_from_trainer
5
  model-index:
6
+ - name: arabert_cross_relevance_task7_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_task7_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:
17
+ - Loss: 0.3047
18
+ - Qwk: 0.0332
19
+ - Mse: 0.3047
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 | 1.2830 | 0.0016 | 1.2830 |
51
+ | No log | 0.2667 | 4 | 0.3134 | 0.0127 | 0.3134 |
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+ | No log | 0.4 | 6 | 0.1648 | 0.1104 | 0.1648 |
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+ | No log | 0.5333 | 8 | 0.1251 | 0.0517 | 0.1251 |
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+ | No log | 0.6667 | 10 | 0.2224 | 0.0017 | 0.2224 |
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+ | No log | 0.8 | 12 | 0.2590 | 0.0094 | 0.2590 |
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+ | No log | 0.9333 | 14 | 0.1796 | 0.0127 | 0.1796 |
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+ | No log | 1.0667 | 16 | 0.1308 | 0.0397 | 0.1308 |
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+ | No log | 1.2 | 18 | 0.1449 | 0.0303 | 0.1449 |
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+ | No log | 1.3333 | 20 | 0.1645 | 0.0288 | 0.1645 |
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+ | No log | 1.4667 | 22 | 0.1859 | 0.0270 | 0.1859 |
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+ | No log | 1.6 | 24 | 0.1923 | 0.0425 | 0.1923 |
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+ | No log | 1.7333 | 26 | 0.1918 | 0.0319 | 0.1918 |
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+ | No log | 1.8667 | 28 | 0.2199 | 0.0290 | 0.2199 |
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+ | No log | 2.0 | 30 | 0.2212 | 0.0273 | 0.2212 |
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+ | No log | 2.1333 | 32 | 0.1858 | 0.0273 | 0.1858 |
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+ | No log | 2.2667 | 34 | 0.1779 | 0.0270 | 0.1779 |
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+ | No log | 2.4 | 36 | 0.2133 | 0.0270 | 0.2133 |
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+ | No log | 2.5333 | 38 | 0.2467 | 0.0339 | 0.2467 |
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+ | No log | 2.6667 | 40 | 0.2211 | 0.0355 | 0.2211 |
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+ | No log | 2.8 | 42 | 0.1890 | 0.0355 | 0.1890 |
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+ | No log | 2.9333 | 44 | 0.2091 | 0.0270 | 0.2091 |
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+ | No log | 3.0667 | 46 | 0.2659 | 0.0254 | 0.2659 |
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+ | No log | 3.2 | 48 | 0.2479 | 0.0235 | 0.2479 |
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+ | No log | 3.3333 | 50 | 0.2076 | 0.0284 | 0.2076 |
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+ | No log | 3.4667 | 52 | 0.1978 | 0.0351 | 0.1978 |
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+ | No log | 3.6 | 54 | 0.2247 | 0.0334 | 0.2247 |
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+ | No log | 3.7333 | 56 | 0.2784 | 0.0319 | 0.2784 |
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+ | No log | 3.8667 | 58 | 0.2815 | 0.0217 | 0.2815 |
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+ | No log | 4.0 | 60 | 0.2597 | 0.0235 | 0.2597 |
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+ | No log | 4.1333 | 62 | 0.2093 | 0.0304 | 0.2093 |
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+ | No log | 4.2667 | 64 | 0.2137 | 0.0287 | 0.2137 |
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+ | No log | 4.4 | 66 | 0.2532 | 0.0235 | 0.2532 |
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+ | No log | 4.5333 | 68 | 0.2399 | 0.0251 | 0.2399 |
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+ | No log | 4.6667 | 70 | 0.2137 | 0.0338 | 0.2137 |
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+ | No log | 4.8 | 72 | 0.2516 | 0.0235 | 0.2516 |
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+ | No log | 4.9333 | 74 | 0.2786 | 0.0319 | 0.2786 |
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+ | No log | 5.0667 | 76 | 0.3017 | 0.0319 | 0.3017 |
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+ | No log | 5.2 | 78 | 0.2701 | 0.0235 | 0.2701 |
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+ | No log | 5.3333 | 80 | 0.2234 | 0.0301 | 0.2234 |
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+ | No log | 5.4667 | 82 | 0.2231 | 0.0301 | 0.2231 |
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+ | No log | 5.6 | 84 | 0.2419 | 0.0284 | 0.2419 |
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+ | No log | 5.7333 | 86 | 0.2839 | 0.0233 | 0.2839 |
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+ | No log | 5.8667 | 88 | 0.2964 | 0.0233 | 0.2964 |
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+ | No log | 6.0 | 90 | 0.2986 | 0.0214 | 0.2986 |
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+ | No log | 6.1333 | 92 | 0.2565 | 0.0317 | 0.2565 |
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+ | No log | 6.2667 | 94 | 0.2203 | 0.0334 | 0.2203 |
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+ | No log | 6.4 | 96 | 0.2553 | 0.0317 | 0.2553 |
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+ | No log | 6.5333 | 98 | 0.3609 | 0.0193 | 0.3609 |
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+ | No log | 6.6667 | 100 | 0.4216 | 0.0206 | 0.4216 |
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+ | No log | 6.8 | 102 | 0.3627 | 0.0225 | 0.3627 |
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+ | No log | 6.9333 | 104 | 0.2543 | 0.0317 | 0.2543 |
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+ | No log | 7.0667 | 106 | 0.2003 | 0.0312 | 0.2003 |
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+ | No log | 7.2 | 108 | 0.2014 | 0.0295 | 0.2014 |
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+ | No log | 7.3333 | 110 | 0.2374 | 0.0301 | 0.2374 |
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+ | No log | 7.4667 | 112 | 0.3176 | 0.0263 | 0.3176 |
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+ | No log | 7.6 | 114 | 0.3811 | 0.0237 | 0.3811 |
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+ | No log | 7.7333 | 116 | 0.3686 | 0.0285 | 0.3686 |
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+ | No log | 7.8667 | 118 | 0.3010 | 0.0260 | 0.3010 |
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+ | No log | 8.0 | 120 | 0.2467 | 0.0317 | 0.2467 |
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+ | No log | 8.1333 | 122 | 0.2371 | 0.0334 | 0.2371 |
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+ | No log | 8.2667 | 124 | 0.2613 | 0.0361 | 0.2613 |
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+ | No log | 8.4 | 126 | 0.2959 | 0.0310 | 0.2959 |
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+ | No log | 8.5333 | 128 | 0.3317 | 0.0225 | 0.3317 |
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+ | No log | 8.6667 | 130 | 0.3288 | 0.0240 | 0.3288 |
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+ | No log | 8.8 | 132 | 0.2998 | 0.0370 | 0.2998 |
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+ | No log | 8.9333 | 134 | 0.2797 | 0.0341 | 0.2797 |
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+ | No log | 9.0667 | 136 | 0.2625 | 0.0441 | 0.2625 |
118
+ | No log | 9.2 | 138 | 0.2672 | 0.0421 | 0.2672 |
119
+ | No log | 9.3333 | 140 | 0.2738 | 0.0421 | 0.2738 |
120
+ | No log | 9.4667 | 142 | 0.2892 | 0.0401 | 0.2892 |
121
+ | No log | 9.6 | 144 | 0.3017 | 0.0366 | 0.3017 |
122
+ | No log | 9.7333 | 146 | 0.3079 | 0.0332 | 0.3079 |
123
+ | No log | 9.8667 | 148 | 0.3065 | 0.0332 | 0.3065 |
124
+ | No log | 10.0 | 150 | 0.3047 | 0.0332 | 0.3047 |
125
 
126
 
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  ### Framework versions
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