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arabert_cross_relevance_task6_fold6

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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_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_task6_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:
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- - Loss: 0.2708
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- - Qwk: 0.2181
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- - Mse: 0.2714
20
 
21
  ## Model description
22
 
@@ -36,49 +36,97 @@ 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
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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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46
  ### Training results
47
 
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- | Training Loss | Epoch | Step | Validation Loss | Qwk | Mse |
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- |:-------------:|:------:|:----:|:---------------:|:------:|:------:|
50
- | No log | 0.0308 | 2 | 0.3997 | 0.1409 | 0.4004 |
51
- | No log | 0.0615 | 4 | 0.3224 | 0.1635 | 0.3230 |
52
- | No log | 0.0923 | 6 | 0.3114 | 0.1336 | 0.3118 |
53
- | No log | 0.1231 | 8 | 0.2792 | 0.1434 | 0.2797 |
54
- | No log | 0.1538 | 10 | 0.5126 | 0.1528 | 0.5116 |
55
- | No log | 0.1846 | 12 | 0.5725 | 0.1322 | 0.5710 |
56
- | No log | 0.2154 | 14 | 0.3291 | 0.2313 | 0.3295 |
57
- | No log | 0.2462 | 16 | 0.2709 | 0.2220 | 0.2712 |
58
- | No log | 0.2769 | 18 | 0.2704 | 0.1746 | 0.2703 |
59
- | No log | 0.3077 | 20 | 0.2714 | 0.1858 | 0.2712 |
60
- | No log | 0.3385 | 22 | 0.2684 | 0.2083 | 0.2682 |
61
- | No log | 0.3692 | 24 | 0.2725 | 0.2135 | 0.2725 |
62
- | No log | 0.4 | 26 | 0.2759 | 0.2135 | 0.2760 |
63
- | No log | 0.4308 | 28 | 0.2785 | 0.2173 | 0.2789 |
64
- | No log | 0.4615 | 30 | 0.2798 | 0.1719 | 0.2803 |
65
- | No log | 0.4923 | 32 | 0.2835 | 0.1711 | 0.2841 |
66
- | No log | 0.5231 | 34 | 0.2859 | 0.1750 | 0.2866 |
67
- | No log | 0.5538 | 36 | 0.2843 | 0.1681 | 0.2850 |
68
- | No log | 0.5846 | 38 | 0.2824 | 0.1738 | 0.2833 |
69
- | No log | 0.6154 | 40 | 0.2828 | 0.2186 | 0.2837 |
70
- | No log | 0.6462 | 42 | 0.2811 | 0.2161 | 0.2821 |
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- | No log | 0.6769 | 44 | 0.2826 | 0.2239 | 0.2836 |
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- | No log | 0.7077 | 46 | 0.2875 | 0.2181 | 0.2884 |
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- | No log | 0.7385 | 48 | 0.2931 | 0.2181 | 0.2940 |
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- | No log | 0.7692 | 50 | 0.2938 | 0.2181 | 0.2947 |
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- | No log | 0.8 | 52 | 0.2942 | 0.2266 | 0.2950 |
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- | No log | 0.8308 | 54 | 0.2868 | 0.2266 | 0.2876 |
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- | No log | 0.8615 | 56 | 0.2800 | 0.2224 | 0.2808 |
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- | No log | 0.8923 | 58 | 0.2751 | 0.2181 | 0.2758 |
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- | No log | 0.9231 | 60 | 0.2725 | 0.2181 | 0.2732 |
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- | No log | 0.9538 | 62 | 0.2712 | 0.2181 | 0.2718 |
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- | No log | 0.9846 | 64 | 0.2708 | 0.2181 | 0.2714 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
82
 
83
 
84
  ### Framework versions
 
3
  tags:
4
  - generated_from_trainer
5
  model-index:
6
+ - name: arabert_cross_relevance_task6_fold5
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_fold5
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: 0.2242
18
+ - Qwk: 0.3701
19
+ - Mse: 0.2242
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
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  - 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 | 0.4047 | 0.2582 | 0.4045 |
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+ | No log | 0.25 | 4 | 0.2750 | 0.5141 | 0.2744 |
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+ | No log | 0.375 | 6 | 0.2556 | 0.3452 | 0.2551 |
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+ | No log | 0.5 | 8 | 0.2742 | 0.2629 | 0.2739 |
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+ | No log | 0.625 | 10 | 0.2556 | 0.2281 | 0.2553 |
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+ | No log | 0.75 | 12 | 0.2574 | 0.2267 | 0.2571 |
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+ | No log | 0.875 | 14 | 0.2555 | 0.3050 | 0.2552 |
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+ | No log | 1.0 | 16 | 0.2258 | 0.2618 | 0.2256 |
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+ | No log | 1.125 | 18 | 0.2150 | 0.3044 | 0.2148 |
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+ | No log | 1.25 | 20 | 0.2079 | 0.3044 | 0.2077 |
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+ | No log | 1.375 | 22 | 0.2022 | 0.3172 | 0.2020 |
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+ | No log | 1.5 | 24 | 0.2011 | 0.3247 | 0.2009 |
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+ | No log | 1.625 | 26 | 0.1872 | 0.3453 | 0.1871 |
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+ | No log | 1.75 | 28 | 0.1813 | 0.3543 | 0.1813 |
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+ | No log | 1.875 | 30 | 0.1764 | 0.3676 | 0.1764 |
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+ | No log | 2.0 | 32 | 0.1744 | 0.4205 | 0.1743 |
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+ | No log | 2.125 | 34 | 0.1788 | 0.4236 | 0.1788 |
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+ | No log | 2.25 | 36 | 0.1817 | 0.3746 | 0.1817 |
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+ | No log | 2.375 | 38 | 0.1911 | 0.4353 | 0.1911 |
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+ | No log | 2.5 | 40 | 0.2063 | 0.6065 | 0.2062 |
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+ | No log | 2.625 | 42 | 0.1851 | 0.4860 | 0.1851 |
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+ | No log | 2.75 | 44 | 0.1768 | 0.3810 | 0.1769 |
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+ | No log | 2.875 | 46 | 0.1839 | 0.3478 | 0.1840 |
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+ | No log | 3.0 | 48 | 0.1903 | 0.3489 | 0.1904 |
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+ | No log | 3.125 | 50 | 0.1887 | 0.3703 | 0.1888 |
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+ | No log | 3.25 | 52 | 0.1832 | 0.3724 | 0.1832 |
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+ | No log | 3.375 | 54 | 0.1852 | 0.3795 | 0.1852 |
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+ | No log | 3.5 | 56 | 0.1937 | 0.4146 | 0.1936 |
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+ | No log | 3.625 | 58 | 0.1934 | 0.3962 | 0.1934 |
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+ | No log | 3.75 | 60 | 0.1920 | 0.3669 | 0.1920 |
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+ | No log | 3.875 | 62 | 0.1930 | 0.4021 | 0.1930 |
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+ | No log | 4.0 | 64 | 0.1970 | 0.4137 | 0.1969 |
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+ | No log | 4.125 | 66 | 0.1944 | 0.4137 | 0.1943 |
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+ | No log | 4.25 | 68 | 0.1936 | 0.3890 | 0.1936 |
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+ | No log | 4.375 | 70 | 0.1981 | 0.3528 | 0.1981 |
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+ | No log | 4.5 | 72 | 0.1927 | 0.3528 | 0.1927 |
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+ | No log | 4.625 | 74 | 0.1928 | 0.3477 | 0.1928 |
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+ | No log | 4.75 | 76 | 0.1965 | 0.3546 | 0.1964 |
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+ | No log | 4.875 | 78 | 0.2095 | 0.3432 | 0.2094 |
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+ | No log | 5.0 | 80 | 0.2044 | 0.3443 | 0.2043 |
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+ | No log | 5.125 | 82 | 0.2006 | 0.3433 | 0.2006 |
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+ | No log | 5.25 | 84 | 0.2036 | 0.3465 | 0.2036 |
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+ | No log | 5.375 | 86 | 0.2052 | 0.3465 | 0.2053 |
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+ | No log | 5.5 | 88 | 0.2022 | 0.3465 | 0.2022 |
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+ | No log | 5.625 | 90 | 0.2017 | 0.3508 | 0.2017 |
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+ | No log | 5.75 | 92 | 0.2073 | 0.3508 | 0.2073 |
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+ | No log | 5.875 | 94 | 0.2122 | 0.3508 | 0.2123 |
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+ | No log | 6.0 | 96 | 0.1997 | 0.3561 | 0.1997 |
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+ | No log | 6.125 | 98 | 0.1967 | 0.3819 | 0.1966 |
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+ | No log | 6.25 | 100 | 0.1968 | 0.3925 | 0.1967 |
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+ | No log | 6.375 | 102 | 0.2088 | 0.3623 | 0.2088 |
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+ | No log | 6.5 | 104 | 0.2513 | 0.3650 | 0.2515 |
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+ | No log | 6.625 | 106 | 0.2811 | 0.3611 | 0.2813 |
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+ | No log | 6.75 | 108 | 0.2626 | 0.3689 | 0.2628 |
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+ | No log | 6.875 | 110 | 0.2260 | 0.3650 | 0.2261 |
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+ | No log | 7.0 | 112 | 0.2040 | 0.3607 | 0.2041 |
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+ | No log | 7.125 | 114 | 0.1937 | 0.3826 | 0.1937 |
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+ | No log | 7.25 | 116 | 0.1925 | 0.3865 | 0.1924 |
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+ | No log | 7.375 | 118 | 0.1942 | 0.3972 | 0.1941 |
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+ | No log | 7.5 | 120 | 0.1957 | 0.3658 | 0.1956 |
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+ | No log | 7.625 | 122 | 0.1993 | 0.3561 | 0.1993 |
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+ | No log | 7.75 | 124 | 0.2083 | 0.3547 | 0.2083 |
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+ | No log | 7.875 | 126 | 0.2197 | 0.3557 | 0.2198 |
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+ | No log | 8.0 | 128 | 0.2322 | 0.3566 | 0.2324 |
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+ | No log | 8.125 | 130 | 0.2346 | 0.3557 | 0.2348 |
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+ | No log | 8.25 | 132 | 0.2299 | 0.3538 | 0.2300 |
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+ | No log | 8.375 | 134 | 0.2254 | 0.3538 | 0.2255 |
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+ | No log | 8.5 | 136 | 0.2201 | 0.3538 | 0.2202 |
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+ | No log | 8.625 | 138 | 0.2148 | 0.3538 | 0.2148 |
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+ | No log | 8.75 | 140 | 0.2117 | 0.3538 | 0.2117 |
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+ | No log | 8.875 | 142 | 0.2123 | 0.3557 | 0.2124 |
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+ | No log | 9.0 | 144 | 0.2127 | 0.3557 | 0.2127 |
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+ | No log | 9.125 | 146 | 0.2153 | 0.3557 | 0.2154 |
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+ | No log | 9.25 | 148 | 0.2195 | 0.3557 | 0.2195 |
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+ | No log | 9.375 | 150 | 0.2224 | 0.3607 | 0.2225 |
125
+ | No log | 9.5 | 152 | 0.2248 | 0.3717 | 0.2249 |
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+ | No log | 9.625 | 154 | 0.2259 | 0.3709 | 0.2260 |
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+ | No log | 9.75 | 156 | 0.2256 | 0.3701 | 0.2257 |
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+ | No log | 9.875 | 158 | 0.2249 | 0.3701 | 0.2249 |
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+ | No log | 10.0 | 160 | 0.2242 | 0.3701 | 0.2242 |
130
 
131
 
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  ### Framework versions
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