Hugging Face's logo

salbatarni
/
arabert_cross_relevance_task2_fold0

TensorBoard
Safetensors
bert
Generated from Trainer
Model card Files Metrics Community
salbatarni commited on
Commit
1eef7a0
•
1 Parent(s): e55ccae

End of training

Browse files
Files changed (1) hide show
  1. README.md +80 -80
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_task1_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_task1_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: 0.3732
18
- - Qwk: 0.2161
19
- - Mse: 0.3733
20
 
21
  ## Model description
22
 
@@ -47,81 +47,81 @@ The following hyperparameters were used during training:
47
 
48
  | Training Loss | Epoch | Step | Validation Loss | Qwk | Mse |
49
  |:-------------:|:------:|:----:|:---------------:|:------:|:------:|
50
- | No log | 0.1333 | 2 | 0.9235 | 0.0305 | 0.9241 |
51
- | No log | 0.2667 | 4 | 0.4213 | 0.0752 | 0.4205 |
52
- | No log | 0.4 | 6 | 0.4900 | 0.2872 | 0.4904 |
53
- | No log | 0.5333 | 8 | 0.3989 | 0.1492 | 0.3997 |
54
- | No log | 0.6667 | 10 | 0.2875 | 0.0828 | 0.2881 |
55
- | No log | 0.8 | 12 | 0.3103 | 0.1946 | 0.3107 |
56
- | No log | 0.9333 | 14 | 0.3505 | 0.1869 | 0.3507 |
57
- | No log | 1.0667 | 16 | 0.2987 | 0.2328 | 0.2991 |
58
- | No log | 1.2 | 18 | 0.2743 | 0.1987 | 0.2749 |
59
- | No log | 1.3333 | 20 | 0.2678 | 0.1801 | 0.2685 |
60
- | No log | 1.4667 | 22 | 0.2718 | 0.2380 | 0.2723 |
61
- | No log | 1.6 | 24 | 0.2750 | 0.2484 | 0.2754 |
62
- | No log | 1.7333 | 26 | 0.2802 | 0.2407 | 0.2807 |
63
- | No log | 1.8667 | 28 | 0.2967 | 0.2647 | 0.2971 |
64
- | No log | 2.0 | 30 | 0.3002 | 0.2386 | 0.3005 |
65
- | No log | 2.1333 | 32 | 0.3042 | 0.2307 | 0.3046 |
66
- | No log | 2.2667 | 34 | 0.2836 | 0.2266 | 0.2840 |
67
- | No log | 2.4 | 36 | 0.2566 | 0.2275 | 0.2571 |
68
- | No log | 2.5333 | 38 | 0.2566 | 0.2726 | 0.2572 |
69
- | No log | 2.6667 | 40 | 0.2685 | 0.2318 | 0.2689 |
70
- | No log | 2.8 | 42 | 0.3239 | 0.2291 | 0.3238 |
71
- | No log | 2.9333 | 44 | 0.3137 | 0.2140 | 0.3139 |
72
- | No log | 3.0667 | 46 | 0.2868 | 0.2462 | 0.2874 |
73
- | No log | 3.2 | 48 | 0.2840 | 0.2475 | 0.2845 |
74
- | No log | 3.3333 | 50 | 0.2972 | 0.2539 | 0.2975 |
75
- | No log | 3.4667 | 52 | 0.2987 | 0.2373 | 0.2989 |
76
- | No log | 3.6 | 54 | 0.2922 | 0.2472 | 0.2925 |
77
- | No log | 3.7333 | 56 | 0.2979 | 0.2276 | 0.2983 |
78
- | No log | 3.8667 | 58 | 0.3082 | 0.2134 | 0.3086 |
79
- | No log | 4.0 | 60 | 0.3245 | 0.2197 | 0.3249 |
80
- | No log | 4.1333 | 62 | 0.3302 | 0.2197 | 0.3305 |
81
- | No log | 4.2667 | 64 | 0.3164 | 0.2079 | 0.3169 |
82
- | No log | 4.4 | 66 | 0.3410 | 0.2131 | 0.3413 |
83
- | No log | 4.5333 | 68 | 0.3844 | 0.2178 | 0.3845 |
84
- | No log | 4.6667 | 70 | 0.3887 | 0.2178 | 0.3888 |
85
- | No log | 4.8 | 72 | 0.3995 | 0.2096 | 0.3996 |
86
- | No log | 4.9333 | 74 | 0.3677 | 0.2141 | 0.3679 |
87
- | No log | 5.0667 | 76 | 0.3517 | 0.2188 | 0.3520 |
88
- | No log | 5.2 | 78 | 0.3437 | 0.2188 | 0.3439 |
89
- | No log | 5.3333 | 80 | 0.3781 | 0.2096 | 0.3782 |
90
- | No log | 5.4667 | 82 | 0.4079 | 0.1975 | 0.4080 |
91
- | No log | 5.6 | 84 | 0.4051 | 0.2133 | 0.4052 |
92
- | No log | 5.7333 | 86 | 0.3469 | 0.2313 | 0.3471 |
93
- | No log | 5.8667 | 88 | 0.3091 | 0.2317 | 0.3095 |
94
- | No log | 6.0 | 90 | 0.3034 | 0.2341 | 0.3039 |
95
- | No log | 6.1333 | 92 | 0.3187 | 0.2175 | 0.3191 |
96
- | No log | 6.2667 | 94 | 0.3556 | 0.2123 | 0.3558 |
97
- | No log | 6.4 | 96 | 0.4256 | 0.1936 | 0.4256 |
98
- | No log | 6.5333 | 98 | 0.4370 | 0.1899 | 0.4370 |
99
- | No log | 6.6667 | 100 | 0.4141 | 0.2053 | 0.4142 |
100
- | No log | 6.8 | 102 | 0.4062 | 0.2053 | 0.4063 |
101
- | No log | 6.9333 | 104 | 0.3722 | 0.2178 | 0.3723 |
102
- | No log | 7.0667 | 106 | 0.3420 | 0.2313 | 0.3423 |
103
- | No log | 7.2 | 108 | 0.3323 | 0.2337 | 0.3326 |
104
- | No log | 7.3333 | 110 | 0.3482 | 0.2161 | 0.3484 |
105
- | No log | 7.4667 | 112 | 0.3690 | 0.2178 | 0.3691 |
106
- | No log | 7.6 | 114 | 0.3867 | 0.2169 | 0.3868 |
107
- | No log | 7.7333 | 116 | 0.4039 | 0.2029 | 0.4039 |
108
- | No log | 7.8667 | 118 | 0.4092 | 0.2029 | 0.4091 |
109
- | No log | 8.0 | 120 | 0.4179 | 0.2012 | 0.4178 |
110
- | No log | 8.1333 | 122 | 0.4160 | 0.2089 | 0.4160 |
111
- | No log | 8.2667 | 124 | 0.4199 | 0.2012 | 0.4199 |
112
- | No log | 8.4 | 126 | 0.4338 | 0.1899 | 0.4337 |
113
- | No log | 8.5333 | 128 | 0.4437 | 0.1935 | 0.4436 |
114
- | No log | 8.6667 | 130 | 0.4404 | 0.1973 | 0.4403 |
115
- | No log | 8.8 | 132 | 0.4283 | 0.2012 | 0.4282 |
116
- | No log | 8.9333 | 134 | 0.4152 | 0.2012 | 0.4151 |
117
- | No log | 9.0667 | 136 | 0.3937 | 0.2089 | 0.3937 |
118
- | No log | 9.2 | 138 | 0.3753 | 0.2141 | 0.3753 |
119
- | No log | 9.3333 | 140 | 0.3664 | 0.2097 | 0.3665 |
120
- | No log | 9.4667 | 142 | 0.3644 | 0.2097 | 0.3645 |
121
- | No log | 9.6 | 144 | 0.3651 | 0.2097 | 0.3652 |
122
- | No log | 9.7333 | 146 | 0.3680 | 0.2097 | 0.3681 |
123
- | No log | 9.8667 | 148 | 0.3713 | 0.2097 | 0.3714 |
124
- | No log | 10.0 | 150 | 0.3732 | 0.2161 | 0.3733 |
125
 
126
 
127
  ### Framework versions
 
3
  tags:
4
  - generated_from_trainer
5
  model-index:
6
+ - name: arabert_cross_relevance_task2_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_relevance_task2_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:
17
+ - Loss: 0.2763
18
+ - Qwk: 0.2118
19
+ - Mse: 0.2766
20
 
21
  ## Model description
22
 
 
47
 
48
  | Training Loss | Epoch | Step | Validation Loss | Qwk | Mse |
49
  |:-------------:|:------:|:----:|:---------------:|:------:|:------:|
50
+ | No log | 0.1333 | 2 | 1.2789 | 0.0139 | 1.2791 |
51
+ | No log | 0.2667 | 4 | 0.3957 | 0.0518 | 0.3957 |
52
+ | No log | 0.4 | 6 | 0.5497 | 0.0762 | 0.5494 |
53
+ | No log | 0.5333 | 8 | 0.5310 | 0.0791 | 0.5312 |
54
+ | No log | 0.6667 | 10 | 0.5062 | 0.0963 | 0.5067 |
55
+ | No log | 0.8 | 12 | 0.3143 | 0.0865 | 0.3147 |
56
+ | No log | 0.9333 | 14 | 0.2566 | 0.0879 | 0.2569 |
57
+ | No log | 1.0667 | 16 | 0.2346 | 0.1763 | 0.2348 |
58
+ | No log | 1.2 | 18 | 0.2326 | 0.0874 | 0.2328 |
59
+ | No log | 1.3333 | 20 | 0.2515 | 0.0751 | 0.2516 |
60
+ | No log | 1.4667 | 22 | 0.2770 | 0.0808 | 0.2772 |
61
+ | No log | 1.6 | 24 | 0.2829 | 0.0971 | 0.2832 |
62
+ | No log | 1.7333 | 26 | 0.2820 | 0.1185 | 0.2824 |
63
+ | No log | 1.8667 | 28 | 0.2898 | 0.2415 | 0.2901 |
64
+ | No log | 2.0 | 30 | 0.2955 | 0.2956 | 0.2958 |
65
+ | No log | 2.1333 | 32 | 0.2854 | 0.1934 | 0.2857 |
66
+ | No log | 2.2667 | 34 | 0.2936 | 0.1068 | 0.2939 |
67
+ | No log | 2.4 | 36 | 0.2771 | 0.1149 | 0.2775 |
68
+ | No log | 2.5333 | 38 | 0.2646 | 0.1251 | 0.2649 |
69
+ | No log | 2.6667 | 40 | 0.2813 | 0.0925 | 0.2816 |
70
+ | No log | 2.8 | 42 | 0.3144 | 0.0962 | 0.3148 |
71
+ | No log | 2.9333 | 44 | 0.2730 | 0.1160 | 0.2734 |
72
+ | No log | 3.0667 | 46 | 0.2608 | 0.1750 | 0.2611 |
73
+ | No log | 3.2 | 48 | 0.2707 | 0.2039 | 0.2710 |
74
+ | No log | 3.3333 | 50 | 0.2810 | 0.1280 | 0.2814 |
75
+ | No log | 3.4667 | 52 | 0.2855 | 0.1188 | 0.2859 |
76
+ | No log | 3.6 | 54 | 0.2726 | 0.1072 | 0.2730 |
77
+ | No log | 3.7333 | 56 | 0.2684 | 0.1361 | 0.2688 |
78
+ | No log | 3.8667 | 58 | 0.2683 | 0.1868 | 0.2686 |
79
+ | No log | 4.0 | 60 | 0.2781 | 0.2062 | 0.2785 |
80
+ | No log | 4.1333 | 62 | 0.2921 | 0.2414 | 0.2924 |
81
+ | No log | 4.2667 | 64 | 0.2977 | 0.2919 | 0.2980 |
82
+ | No log | 4.4 | 66 | 0.2977 | 0.2571 | 0.2980 |
83
+ | No log | 4.5333 | 68 | 0.2869 | 0.2312 | 0.2872 |
84
+ | No log | 4.6667 | 70 | 0.2721 | 0.2289 | 0.2724 |
85
+ | No log | 4.8 | 72 | 0.2696 | 0.2253 | 0.2699 |
86
+ | No log | 4.9333 | 74 | 0.2755 | 0.1581 | 0.2759 |
87
+ | No log | 5.0667 | 76 | 0.2782 | 0.1567 | 0.2786 |
88
+ | No log | 5.2 | 78 | 0.2752 | 0.1686 | 0.2756 |
89
+ | No log | 5.3333 | 80 | 0.2765 | 0.1716 | 0.2769 |
90
+ | No log | 5.4667 | 82 | 0.2686 | 0.2142 | 0.2690 |
91
+ | No log | 5.6 | 84 | 0.2667 | 0.2265 | 0.2670 |
92
+ | No log | 5.7333 | 86 | 0.2752 | 0.2050 | 0.2756 |
93
+ | No log | 5.8667 | 88 | 0.2867 | 0.1803 | 0.2871 |
94
+ | No log | 6.0 | 90 | 0.2816 | 0.2116 | 0.2819 |
95
+ | No log | 6.1333 | 92 | 0.2723 | 0.2557 | 0.2726 |
96
+ | No log | 6.2667 | 94 | 0.2733 | 0.2884 | 0.2735 |
97
+ | No log | 6.4 | 96 | 0.2753 | 0.2629 | 0.2755 |
98
+ | No log | 6.5333 | 98 | 0.2787 | 0.2101 | 0.2790 |
99
+ | No log | 6.6667 | 100 | 0.2860 | 0.1805 | 0.2863 |
100
+ | No log | 6.8 | 102 | 0.2870 | 0.1727 | 0.2873 |
101
+ | No log | 6.9333 | 104 | 0.2680 | 0.1702 | 0.2683 |
102
+ | No log | 7.0667 | 106 | 0.2577 | 0.1767 | 0.2579 |
103
+ | No log | 7.2 | 108 | 0.2595 | 0.1735 | 0.2598 |
104
+ | No log | 7.3333 | 110 | 0.2638 | 0.1751 | 0.2640 |
105
+ | No log | 7.4667 | 112 | 0.2779 | 0.1759 | 0.2782 |
106
+ | No log | 7.6 | 114 | 0.2860 | 0.1726 | 0.2864 |
107
+ | No log | 7.7333 | 116 | 0.2810 | 0.1757 | 0.2813 |
108
+ | No log | 7.8667 | 118 | 0.2683 | 0.1912 | 0.2686 |
109
+ | No log | 8.0 | 120 | 0.2616 | 0.2129 | 0.2618 |
110
+ | No log | 8.1333 | 122 | 0.2606 | 0.2129 | 0.2608 |
111
+ | No log | 8.2667 | 124 | 0.2651 | 0.2043 | 0.2654 |
112
+ | No log | 8.4 | 126 | 0.2700 | 0.1970 | 0.2703 |
113
+ | No log | 8.5333 | 128 | 0.2737 | 0.1914 | 0.2741 |
114
+ | No log | 8.6667 | 130 | 0.2727 | 0.2139 | 0.2731 |
115
+ | No log | 8.8 | 132 | 0.2748 | 0.2139 | 0.2751 |
116
+ | No log | 8.9333 | 134 | 0.2738 | 0.2175 | 0.2741 |
117
+ | No log | 9.0667 | 136 | 0.2726 | 0.2112 | 0.2730 |
118
+ | No log | 9.2 | 138 | 0.2719 | 0.2166 | 0.2722 |
119
+ | No log | 9.3333 | 140 | 0.2710 | 0.2275 | 0.2713 |
120
+ | No log | 9.4667 | 142 | 0.2714 | 0.2275 | 0.2717 |
121
+ | No log | 9.6 | 144 | 0.2724 | 0.2242 | 0.2727 |
122
+ | No log | 9.7333 | 146 | 0.2742 | 0.2154 | 0.2745 |
123
+ | No log | 9.8667 | 148 | 0.2755 | 0.2118 | 0.2758 |
124
+ | No log | 10.0 | 150 | 0.2763 | 0.2118 | 0.2766 |
125
 
126
 
127
  ### Framework versions