Hugging Face's logo

MayBashendy
/
ArabicNewSplits7_usingWellWrittenEssays_FineTuningAraBERT_run2_AugV5_k17_task2_organization

Text Classification
Transformers
Safetensors
bert
Generated from Trainer
Model card Files
xet
 Community
MayBashendy commited on
Commit
269efb1
·
verified ·
1 Parent(s): a733773

Training in progress, step 500

Browse files
Files changed (4) hide show
  1. README.md +316 -0
  2. config.json +32 -0
  3. model.safetensors +3 -0
  4. training_args.bin +3 -0
README.md ADDED
@@ -0,0 +1,316 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ library_name: transformers
3
+ base_model: aubmindlab/bert-base-arabertv02
4
+ tags:
5
+ - generated_from_trainer
6
+ model-index:
7
+ - name: ArabicNewSplits7_usingWellWrittenEssays_FineTuningAraBERT_run2_AugV5_k16_task2_organization
8
+ results: []
9
+ ---
10
+
11
+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
12
+ should probably proofread and complete it, then remove this comment. -->
13
+
14
+ # ArabicNewSplits7_usingWellWrittenEssays_FineTuningAraBERT_run2_AugV5_k16_task2_organization
15
+
16
+ This model is a fine-tuned version of [aubmindlab/bert-base-arabertv02](https://huggingface.co/aubmindlab/bert-base-arabertv02) on the None dataset.
17
+ It achieves the following results on the evaluation set:
18
+ - Loss: 1.3240
19
+ - Qwk: 0.0887
20
+ - Mse: 1.3240
21
+ - Rmse: 1.1507
22
+
23
+ ## Model description
24
+
25
+ More information needed
26
+
27
+ ## Intended uses & limitations
28
+
29
+ More information needed
30
+
31
+ ## Training and evaluation data
32
+
33
+ More information needed
34
+
35
+ ## Training procedure
36
+
37
+ ### Training hyperparameters
38
+
39
+ The following hyperparameters were used during training:
40
+ - learning_rate: 2e-05
41
+ - train_batch_size: 8
42
+ - eval_batch_size: 8
43
+ - seed: 42
44
+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
45
+ - lr_scheduler_type: linear
46
+ - num_epochs: 100
47
+
48
+ ### Training results
49
+
50
+ | Training Loss | Epoch | Step | Validation Loss | Qwk | Mse | Rmse |
51
+ |:-------------:|:-------:|:----:|:---------------:|:-------:|:------:|:------:|
52
+ | No log | 0.0435 | 2 | 4.5392 | -0.0132 | 4.5392 | 2.1305 |
53
+ | No log | 0.0870 | 4 | 2.6144 | 0.0025 | 2.6144 | 1.6169 |
54
+ | No log | 0.1304 | 6 | 2.0477 | -0.0634 | 2.0477 | 1.4310 |
55
+ | No log | 0.1739 | 8 | 2.4964 | -0.0777 | 2.4964 | 1.5800 |
56
+ | No log | 0.2174 | 10 | 1.6546 | 0.0596 | 1.6546 | 1.2863 |
57
+ | No log | 0.2609 | 12 | 1.2478 | 0.1990 | 1.2478 | 1.1170 |
58
+ | No log | 0.3043 | 14 | 1.2637 | -0.0010 | 1.2637 | 1.1241 |
59
+ | No log | 0.3478 | 16 | 1.3075 | -0.0114 | 1.3075 | 1.1435 |
60
+ | No log | 0.3913 | 18 | 1.1879 | 0.2180 | 1.1879 | 1.0899 |
61
+ | No log | 0.4348 | 20 | 1.0978 | 0.3307 | 1.0978 | 1.0478 |
62
+ | No log | 0.4783 | 22 | 1.2352 | 0.1106 | 1.2352 | 1.1114 |
63
+ | No log | 0.5217 | 24 | 1.7188 | 0.1277 | 1.7188 | 1.3110 |
64
+ | No log | 0.5652 | 26 | 1.6947 | 0.1827 | 1.6947 | 1.3018 |
65
+ | No log | 0.6087 | 28 | 1.4720 | 0.1604 | 1.4720 | 1.2133 |
66
+ | No log | 0.6522 | 30 | 1.2747 | 0.1168 | 1.2747 | 1.1290 |
67
+ | No log | 0.6957 | 32 | 1.2740 | 0.1904 | 1.2740 | 1.1287 |
68
+ | No log | 0.7391 | 34 | 1.3932 | 0.1016 | 1.3932 | 1.1803 |
69
+ | No log | 0.7826 | 36 | 1.5722 | 0.0723 | 1.5722 | 1.2539 |
70
+ | No log | 0.8261 | 38 | 1.6145 | 0.0084 | 1.6145 | 1.2706 |
71
+ | No log | 0.8696 | 40 | 1.5704 | 0.0084 | 1.5704 | 1.2531 |
72
+ | No log | 0.9130 | 42 | 1.5551 | 0.0084 | 1.5551 | 1.2470 |
73
+ | No log | 0.9565 | 44 | 1.4364 | 0.0488 | 1.4364 | 1.1985 |
74
+ | No log | 1.0 | 46 | 1.2243 | 0.3135 | 1.2243 | 1.1065 |
75
+ | No log | 1.0435 | 48 | 1.1501 | 0.2678 | 1.1501 | 1.0724 |
76
+ | No log | 1.0870 | 50 | 1.2350 | 0.0918 | 1.2350 | 1.1113 |
77
+ | No log | 1.1304 | 52 | 1.2402 | 0.1080 | 1.2402 | 1.1136 |
78
+ | No log | 1.1739 | 54 | 1.2115 | 0.2188 | 1.2115 | 1.1007 |
79
+ | No log | 1.2174 | 56 | 1.2436 | 0.2188 | 1.2436 | 1.1152 |
80
+ | No log | 1.2609 | 58 | 1.2801 | 0.2188 | 1.2801 | 1.1314 |
81
+ | No log | 1.3043 | 60 | 1.3568 | 0.1246 | 1.3568 | 1.1648 |
82
+ | No log | 1.3478 | 62 | 1.3834 | 0.1085 | 1.3834 | 1.1762 |
83
+ | No log | 1.3913 | 64 | 1.3154 | 0.2123 | 1.3154 | 1.1469 |
84
+ | No log | 1.4348 | 66 | 1.2935 | 0.2310 | 1.2935 | 1.1373 |
85
+ | No log | 1.4783 | 68 | 1.3649 | 0.1251 | 1.3649 | 1.1683 |
86
+ | No log | 1.5217 | 70 | 1.5057 | 0.1499 | 1.5057 | 1.2271 |
87
+ | No log | 1.5652 | 72 | 1.5639 | 0.1499 | 1.5639 | 1.2505 |
88
+ | No log | 1.6087 | 74 | 1.3761 | 0.2695 | 1.3761 | 1.1731 |
89
+ | No log | 1.6522 | 76 | 1.2028 | 0.2831 | 1.2028 | 1.0967 |
90
+ | No log | 1.6957 | 78 | 1.1560 | 0.2318 | 1.1560 | 1.0752 |
91
+ | No log | 1.7391 | 80 | 1.2434 | 0.3478 | 1.2434 | 1.1151 |
92
+ | No log | 1.7826 | 82 | 1.2869 | 0.3227 | 1.2869 | 1.1344 |
93
+ | No log | 1.8261 | 84 | 1.4592 | 0.2378 | 1.4592 | 1.2080 |
94
+ | No log | 1.8696 | 86 | 1.2396 | 0.4078 | 1.2396 | 1.1134 |
95
+ | No log | 1.9130 | 88 | 1.1017 | 0.4841 | 1.1017 | 1.0496 |
96
+ | No log | 1.9565 | 90 | 1.1531 | 0.4716 | 1.1531 | 1.0738 |
97
+ | No log | 2.0 | 92 | 1.6415 | 0.1373 | 1.6415 | 1.2812 |
98
+ | No log | 2.0435 | 94 | 2.0876 | 0.0091 | 2.0876 | 1.4449 |
99
+ | No log | 2.0870 | 96 | 2.0196 | 0.0608 | 2.0196 | 1.4211 |
100
+ | No log | 2.1304 | 98 | 1.5143 | 0.1087 | 1.5143 | 1.2306 |
101
+ | No log | 2.1739 | 100 | 1.0257 | 0.3144 | 1.0257 | 1.0128 |
102
+ | No log | 2.2174 | 102 | 0.8991 | 0.4002 | 0.8991 | 0.9482 |
103
+ | No log | 2.2609 | 104 | 0.9778 | 0.3389 | 0.9778 | 0.9888 |
104
+ | No log | 2.3043 | 106 | 1.2040 | 0.1404 | 1.2040 | 1.0972 |
105
+ | No log | 2.3478 | 108 | 1.4502 | 0.2373 | 1.4502 | 1.2043 |
106
+ | No log | 2.3913 | 110 | 1.4162 | 0.2445 | 1.4162 | 1.1900 |
107
+ | No log | 2.4348 | 112 | 1.2399 | 0.2213 | 1.2399 | 1.1135 |
108
+ | No log | 2.4783 | 114 | 1.0548 | 0.2619 | 1.0548 | 1.0270 |
109
+ | No log | 2.5217 | 116 | 1.0567 | 0.3657 | 1.0567 | 1.0279 |
110
+ | No log | 2.5652 | 118 | 1.2290 | 0.4075 | 1.2290 | 1.1086 |
111
+ | No log | 2.6087 | 120 | 1.4256 | 0.4050 | 1.4256 | 1.1940 |
112
+ | No log | 2.6522 | 122 | 1.6952 | 0.1672 | 1.6952 | 1.3020 |
113
+ | No log | 2.6957 | 124 | 1.6455 | 0.1885 | 1.6455 | 1.2828 |
114
+ | No log | 2.7391 | 126 | 1.2541 | 0.4112 | 1.2541 | 1.1199 |
115
+ | No log | 2.7826 | 128 | 1.1299 | 0.4803 | 1.1299 | 1.0630 |
116
+ | No log | 2.8261 | 130 | 1.1623 | 0.4487 | 1.1623 | 1.0781 |
117
+ | No log | 2.8696 | 132 | 1.2953 | 0.3926 | 1.2953 | 1.1381 |
118
+ | No log | 2.9130 | 134 | 1.1062 | 0.3540 | 1.1062 | 1.0517 |
119
+ | No log | 2.9565 | 136 | 0.9813 | 0.2782 | 0.9813 | 0.9906 |
120
+ | No log | 3.0 | 138 | 0.9605 | 0.3122 | 0.9605 | 0.9801 |
121
+ | No log | 3.0435 | 140 | 0.9383 | 0.3122 | 0.9383 | 0.9686 |
122
+ | No log | 3.0870 | 142 | 0.9192 | 0.3463 | 0.9192 | 0.9588 |
123
+ | No log | 3.1304 | 144 | 0.9387 | 0.3069 | 0.9387 | 0.9689 |
124
+ | No log | 3.1739 | 146 | 0.9361 | 0.2997 | 0.9361 | 0.9675 |
125
+ | No log | 3.2174 | 148 | 0.9828 | 0.3492 | 0.9828 | 0.9914 |
126
+ | No log | 3.2609 | 150 | 1.1013 | 0.3528 | 1.1013 | 1.0494 |
127
+ | No log | 3.3043 | 152 | 1.2506 | 0.2870 | 1.2506 | 1.1183 |
128
+ | No log | 3.3478 | 154 | 1.3671 | 0.2544 | 1.3671 | 1.1692 |
129
+ | No log | 3.3913 | 156 | 1.6324 | 0.2632 | 1.6324 | 1.2777 |
130
+ | No log | 3.4348 | 158 | 1.6640 | 0.2574 | 1.6640 | 1.2900 |
131
+ | No log | 3.4783 | 160 | 1.6062 | 0.1704 | 1.6062 | 1.2673 |
132
+ | No log | 3.5217 | 162 | 1.4258 | 0.1698 | 1.4258 | 1.1941 |
133
+ | No log | 3.5652 | 164 | 1.1820 | 0.2015 | 1.1820 | 1.0872 |
134
+ | No log | 3.6087 | 166 | 1.1163 | 0.2432 | 1.1163 | 1.0566 |
135
+ | No log | 3.6522 | 168 | 1.1634 | 0.2313 | 1.1634 | 1.0786 |
136
+ | No log | 3.6957 | 170 | 1.4733 | 0.2512 | 1.4733 | 1.2138 |
137
+ | No log | 3.7391 | 172 | 1.7133 | 0.1149 | 1.7133 | 1.3089 |
138
+ | No log | 3.7826 | 174 | 1.7287 | 0.0841 | 1.7287 | 1.3148 |
139
+ | No log | 3.8261 | 176 | 1.6828 | 0.1961 | 1.6828 | 1.2972 |
140
+ | No log | 3.8696 | 178 | 1.5252 | 0.2789 | 1.5252 | 1.2350 |
141
+ | No log | 3.9130 | 180 | 1.2831 | 0.3136 | 1.2831 | 1.1327 |
142
+ | No log | 3.9565 | 182 | 1.2904 | 0.2634 | 1.2904 | 1.1359 |
143
+ | No log | 4.0 | 184 | 1.3169 | 0.2527 | 1.3169 | 1.1476 |
144
+ | No log | 4.0435 | 186 | 1.4300 | 0.3025 | 1.4300 | 1.1958 |
145
+ | No log | 4.0870 | 188 | 1.4173 | 0.2617 | 1.4173 | 1.1905 |
146
+ | No log | 4.1304 | 190 | 1.2387 | 0.2864 | 1.2387 | 1.1130 |
147
+ | No log | 4.1739 | 192 | 1.0969 | 0.2236 | 1.0969 | 1.0473 |
148
+ | No log | 4.2174 | 194 | 1.1665 | 0.2864 | 1.1665 | 1.0801 |
149
+ | No log | 4.2609 | 196 | 1.3768 | 0.2252 | 1.3768 | 1.1734 |
150
+ | No log | 4.3043 | 198 | 1.4031 | 0.1935 | 1.4031 | 1.1845 |
151
+ | No log | 4.3478 | 200 | 1.3006 | 0.1345 | 1.3006 | 1.1404 |
152
+ | No log | 4.3913 | 202 | 1.2641 | 0.2570 | 1.2641 | 1.1243 |
153
+ | No log | 4.4348 | 204 | 1.1540 | 0.1952 | 1.1540 | 1.0742 |
154
+ | No log | 4.4783 | 206 | 1.0314 | 0.2446 | 1.0314 | 1.0156 |
155
+ | No log | 4.5217 | 208 | 0.9837 | 0.2574 | 0.9838 | 0.9918 |
156
+ | No log | 4.5652 | 210 | 1.1298 | 0.3398 | 1.1298 | 1.0629 |
157
+ | No log | 4.6087 | 212 | 1.4698 | 0.3302 | 1.4698 | 1.2123 |
158
+ | No log | 4.6522 | 214 | 1.6554 | 0.2217 | 1.6554 | 1.2866 |
159
+ | No log | 4.6957 | 216 | 1.5817 | 0.1051 | 1.5817 | 1.2577 |
160
+ | No log | 4.7391 | 218 | 1.3478 | 0.1031 | 1.3478 | 1.1609 |
161
+ | No log | 4.7826 | 220 | 1.1472 | 0.1219 | 1.1472 | 1.0711 |
162
+ | No log | 4.8261 | 222 | 1.0065 | 0.2761 | 1.0065 | 1.0033 |
163
+ | No log | 4.8696 | 224 | 0.9602 | 0.3271 | 0.9602 | 0.9799 |
164
+ | No log | 4.9130 | 226 | 0.9673 | 0.2871 | 0.9673 | 0.9835 |
165
+ | No log | 4.9565 | 228 | 1.0335 | 0.3584 | 1.0335 | 1.0166 |
166
+ | No log | 5.0 | 230 | 1.3019 | 0.2701 | 1.3019 | 1.1410 |
167
+ | No log | 5.0435 | 232 | 1.5644 | 0.3371 | 1.5644 | 1.2508 |
168
+ | No log | 5.0870 | 234 | 1.5612 | 0.3572 | 1.5612 | 1.2495 |
169
+ | No log | 5.1304 | 236 | 1.2730 | 0.2903 | 1.2730 | 1.1283 |
170
+ | No log | 5.1739 | 238 | 1.0605 | 0.3394 | 1.0605 | 1.0298 |
171
+ | No log | 5.2174 | 240 | 1.0279 | 0.3572 | 1.0279 | 1.0139 |
172
+ | No log | 5.2609 | 242 | 1.0334 | 0.3572 | 1.0334 | 1.0165 |
173
+ | No log | 5.3043 | 244 | 1.0897 | 0.3182 | 1.0897 | 1.0439 |
174
+ | No log | 5.3478 | 246 | 1.1933 | 0.2664 | 1.1933 | 1.0924 |
175
+ | No log | 5.3913 | 248 | 1.3541 | 0.2632 | 1.3541 | 1.1637 |
176
+ | No log | 5.4348 | 250 | 1.3200 | 0.1886 | 1.3200 | 1.1489 |
177
+ | No log | 5.4783 | 252 | 1.1635 | 0.2131 | 1.1635 | 1.0787 |
178
+ | No log | 5.5217 | 254 | 1.0955 | 0.2927 | 1.0955 | 1.0467 |
179
+ | No log | 5.5652 | 256 | 1.0594 | 0.3217 | 1.0594 | 1.0293 |
180
+ | No log | 5.6087 | 258 | 1.1165 | 0.2743 | 1.1165 | 1.0566 |
181
+ | No log | 5.6522 | 260 | 1.3771 | 0.2009 | 1.3771 | 1.1735 |
182
+ | No log | 5.6957 | 262 | 1.5092 | 0.3173 | 1.5092 | 1.2285 |
183
+ | No log | 5.7391 | 264 | 1.4651 | 0.3157 | 1.4651 | 1.2104 |
184
+ | No log | 5.7826 | 266 | 1.3156 | 0.2359 | 1.3156 | 1.1470 |
185
+ | No log | 5.8261 | 268 | 1.1553 | 0.2743 | 1.1553 | 1.0748 |
186
+ | No log | 5.8696 | 270 | 1.1775 | 0.2367 | 1.1775 | 1.0851 |
187
+ | No log | 5.9130 | 272 | 1.2517 | 0.1935 | 1.2517 | 1.1188 |
188
+ | No log | 5.9565 | 274 | 1.2168 | 0.1935 | 1.2168 | 1.1031 |
189
+ | No log | 6.0 | 276 | 1.1152 | 0.2402 | 1.1152 | 1.0560 |
190
+ | No log | 6.0435 | 278 | 1.1285 | 0.2475 | 1.1285 | 1.0623 |
191
+ | No log | 6.0870 | 280 | 1.2532 | 0.2617 | 1.2532 | 1.1195 |
192
+ | No log | 6.1304 | 282 | 1.4690 | 0.2632 | 1.4690 | 1.2120 |
193
+ | No log | 6.1739 | 284 | 1.6400 | 0.3219 | 1.6400 | 1.2806 |
194
+ | No log | 6.2174 | 286 | 1.5979 | 0.3383 | 1.5979 | 1.2641 |
195
+ | No log | 6.2609 | 288 | 1.3254 | 0.2903 | 1.3254 | 1.1513 |
196
+ | No log | 6.3043 | 290 | 1.1477 | 0.3438 | 1.1477 | 1.0713 |
197
+ | No log | 6.3478 | 292 | 1.0508 | 0.2998 | 1.0508 | 1.0251 |
198
+ | No log | 6.3913 | 294 | 1.1049 | 0.2930 | 1.1049 | 1.0511 |
199
+ | No log | 6.4348 | 296 | 1.2790 | 0.2586 | 1.2790 | 1.1309 |
200
+ | No log | 6.4783 | 298 | 1.3121 | 0.2173 | 1.3121 | 1.1455 |
201
+ | No log | 6.5217 | 300 | 1.2595 | 0.1745 | 1.2595 | 1.1223 |
202
+ | No log | 6.5652 | 302 | 1.1685 | 0.1538 | 1.1685 | 1.0810 |
203
+ | No log | 6.6087 | 304 | 1.1663 | 0.1538 | 1.1663 | 1.0799 |
204
+ | No log | 6.6522 | 306 | 1.1214 | 0.1696 | 1.1214 | 1.0589 |
205
+ | No log | 6.6957 | 308 | 1.2074 | 0.1637 | 1.2074 | 1.0988 |
206
+ | No log | 6.7391 | 310 | 1.2648 | 0.1440 | 1.2648 | 1.1246 |
207
+ | No log | 6.7826 | 312 | 1.3777 | 0.1345 | 1.3777 | 1.1737 |
208
+ | No log | 6.8261 | 314 | 1.3739 | 0.1345 | 1.3739 | 1.1722 |
209
+ | No log | 6.8696 | 316 | 1.2697 | 0.1031 | 1.2697 | 1.1268 |
210
+ | No log | 6.9130 | 318 | 1.1635 | 0.1440 | 1.1635 | 1.0787 |
211
+ | No log | 6.9565 | 320 | 1.0852 | 0.1853 | 1.0852 | 1.0417 |
212
+ | No log | 7.0 | 322 | 1.1148 | 0.1596 | 1.1148 | 1.0558 |
213
+ | No log | 7.0435 | 324 | 1.1851 | 0.1889 | 1.1851 | 1.0886 |
214
+ | No log | 7.0870 | 326 | 1.2449 | 0.2213 | 1.2449 | 1.1158 |
215
+ | No log | 7.1304 | 328 | 1.2107 | 0.2512 | 1.2107 | 1.1003 |
216
+ | No log | 7.1739 | 330 | 1.0905 | 0.3046 | 1.0905 | 1.0443 |
217
+ | No log | 7.2174 | 332 | 1.0588 | 0.2857 | 1.0588 | 1.0290 |
218
+ | No log | 7.2609 | 334 | 1.1178 | 0.2602 | 1.1178 | 1.0573 |
219
+ | No log | 7.3043 | 336 | 1.2510 | 0.2512 | 1.2510 | 1.1185 |
220
+ | No log | 7.3478 | 338 | 1.3561 | 0.3220 | 1.3561 | 1.1645 |
221
+ | No log | 7.3913 | 340 | 1.2888 | 0.2512 | 1.2888 | 1.1352 |
222
+ | No log | 7.4348 | 342 | 1.0695 | 0.2250 | 1.0695 | 1.0342 |
223
+ | No log | 7.4783 | 344 | 1.0304 | 0.2417 | 1.0304 | 1.0151 |
224
+ | No log | 7.5217 | 346 | 1.1582 | 0.2348 | 1.1582 | 1.0762 |
225
+ | No log | 7.5652 | 348 | 1.2684 | 0.2844 | 1.2684 | 1.1262 |
226
+ | No log | 7.6087 | 350 | 1.3202 | 0.2479 | 1.3202 | 1.1490 |
227
+ | No log | 7.6522 | 352 | 1.2723 | 0.2317 | 1.2723 | 1.1280 |
228
+ | No log | 7.6957 | 354 | 1.2150 | 0.2278 | 1.2150 | 1.1023 |
229
+ | No log | 7.7391 | 356 | 1.0981 | 0.2046 | 1.0981 | 1.0479 |
230
+ | No log | 7.7826 | 358 | 0.9789 | 0.2219 | 0.9789 | 0.9894 |
231
+ | No log | 7.8261 | 360 | 0.9571 | 0.2219 | 0.9571 | 0.9783 |
232
+ | No log | 7.8696 | 362 | 1.0565 | 0.2884 | 1.0565 | 1.0279 |
233
+ | No log | 7.9130 | 364 | 1.2201 | 0.2725 | 1.2201 | 1.1046 |
234
+ | No log | 7.9565 | 366 | 1.2609 | 0.2586 | 1.2609 | 1.1229 |
235
+ | No log | 8.0 | 368 | 1.1853 | 0.1896 | 1.1853 | 1.0887 |
236
+ | No log | 8.0435 | 370 | 1.1160 | 0.2108 | 1.1160 | 1.0564 |
237
+ | No log | 8.0870 | 372 | 1.1039 | 0.1417 | 1.1039 | 1.0507 |
238
+ | No log | 8.1304 | 374 | 1.1157 | 0.0974 | 1.1157 | 1.0563 |
239
+ | No log | 8.1739 | 376 | 1.1743 | 0.1596 | 1.1743 | 1.0836 |
240
+ | No log | 8.2174 | 378 | 1.1340 | 0.2195 | 1.1340 | 1.0649 |
241
+ | No log | 8.2609 | 380 | 1.0263 | 0.2650 | 1.0263 | 1.0131 |
242
+ | No log | 8.3043 | 382 | 0.8891 | 0.3217 | 0.8891 | 0.9429 |
243
+ | No log | 8.3478 | 384 | 0.8458 | 0.4282 | 0.8458 | 0.9197 |
244
+ | No log | 8.3913 | 386 | 0.8776 | 0.3753 | 0.8776 | 0.9368 |
245
+ | No log | 8.4348 | 388 | 0.9996 | 0.2654 | 0.9996 | 0.9998 |
246
+ | No log | 8.4783 | 390 | 1.2150 | 0.2330 | 1.2150 | 1.1023 |
247
+ | No log | 8.5217 | 392 | 1.3036 | 0.2696 | 1.3036 | 1.1418 |
248
+ | No log | 8.5652 | 394 | 1.3130 | 0.1889 | 1.3130 | 1.1459 |
249
+ | No log | 8.6087 | 396 | 1.2895 | 0.1889 | 1.2895 | 1.1355 |
250
+ | No log | 8.6522 | 398 | 1.2319 | 0.1500 | 1.2319 | 1.1099 |
251
+ | No log | 8.6957 | 400 | 1.1813 | 0.1379 | 1.1813 | 1.0869 |
252
+ | No log | 8.7391 | 402 | 1.2000 | 0.1379 | 1.2000 | 1.0954 |
253
+ | No log | 8.7826 | 404 | 1.2050 | 0.1185 | 1.2050 | 1.0977 |
254
+ | No log | 8.8261 | 406 | 1.2323 | 0.1500 | 1.2323 | 1.1101 |
255
+ | No log | 8.8696 | 408 | 1.2384 | 0.2184 | 1.2384 | 1.1128 |
256
+ | No log | 8.9130 | 410 | 1.1928 | 0.2602 | 1.1928 | 1.0922 |
257
+ | No log | 8.9565 | 412 | 1.2004 | 0.3115 | 1.2004 | 1.0956 |
258
+ | No log | 9.0 | 414 | 1.1146 | 0.2857 | 1.1146 | 1.0558 |
259
+ | No log | 9.0435 | 416 | 1.0278 | 0.1808 | 1.0278 | 1.0138 |
260
+ | No log | 9.0870 | 418 | 1.0516 | 0.1602 | 1.0516 | 1.0255 |
261
+ | No log | 9.1304 | 420 | 1.1158 | 0.1903 | 1.1158 | 1.0563 |
262
+ | No log | 9.1739 | 422 | 1.1210 | 0.1903 | 1.1210 | 1.0588 |
263
+ | No log | 9.2174 | 424 | 1.1783 | 0.1750 | 1.1783 | 1.0855 |
264
+ | No log | 9.2609 | 426 | 1.2273 | 0.2317 | 1.2273 | 1.1079 |
265
+ | No log | 9.3043 | 428 | 1.1979 | 0.1440 | 1.1979 | 1.0945 |
266
+ | No log | 9.3478 | 430 | 1.1255 | 0.1952 | 1.1255 | 1.0609 |
267
+ | No log | 9.3913 | 432 | 1.0807 | 0.1417 | 1.0807 | 1.0396 |
268
+ | No log | 9.4348 | 434 | 1.0993 | 0.1247 | 1.0993 | 1.0485 |
269
+ | No log | 9.4783 | 436 | 1.1346 | 0.1846 | 1.1346 | 1.0652 |
270
+ | No log | 9.5217 | 438 | 1.1270 | 0.2439 | 1.1270 | 1.0616 |
271
+ | No log | 9.5652 | 440 | 1.0935 | 0.2439 | 1.0935 | 1.0457 |
272
+ | No log | 9.6087 | 442 | 1.0726 | 0.2651 | 1.0726 | 1.0356 |
273
+ | No log | 9.6522 | 444 | 1.1045 | 0.2439 | 1.1045 | 1.0510 |
274
+ | No log | 9.6957 | 446 | 1.0993 | 0.2051 | 1.0993 | 1.0485 |
275
+ | No log | 9.7391 | 448 | 1.0528 | 0.1480 | 1.0528 | 1.0260 |
276
+ | No log | 9.7826 | 450 | 1.0315 | 0.1645 | 1.0315 | 1.0156 |
277
+ | No log | 9.8261 | 452 | 1.0807 | 0.1952 | 1.0807 | 1.0396 |
278
+ | No log | 9.8696 | 454 | 1.1966 | 0.2553 | 1.1966 | 1.0939 |
279
+ | No log | 9.9130 | 456 | 1.2671 | 0.2707 | 1.2671 | 1.1256 |
280
+ | No log | 9.9565 | 458 | 1.2297 | 0.3433 | 1.2297 | 1.1089 |
281
+ | No log | 10.0 | 460 | 1.0999 | 0.2837 | 1.0999 | 1.0488 |
282
+ | No log | 10.0435 | 462 | 1.0677 | 0.2743 | 1.0677 | 1.0333 |
283
+ | No log | 10.0870 | 464 | 1.1248 | 0.2837 | 1.1248 | 1.0606 |
284
+ | No log | 10.1304 | 466 | 1.1626 | 0.1991 | 1.1626 | 1.0782 |
285
+ | No log | 10.1739 | 468 | 1.1976 | 0.1440 | 1.1976 | 1.0944 |
286
+ | No log | 10.2174 | 470 | 1.1848 | 0.1637 | 1.1848 | 1.0885 |
287
+ | No log | 10.2609 | 472 | 1.1426 | 0.0904 | 1.1426 | 1.0689 |
288
+ | No log | 10.3043 | 474 | 1.1291 | 0.0904 | 1.1291 | 1.0626 |
289
+ | No log | 10.3478 | 476 | 1.1291 | 0.1122 | 1.1291 | 1.0626 |
290
+ | No log | 10.3913 | 478 | 1.2456 | 0.2278 | 1.2456 | 1.1161 |
291
+ | No log | 10.4348 | 480 | 1.3021 | 0.2553 | 1.3021 | 1.1411 |
292
+ | No log | 10.4783 | 482 | 1.4101 | 0.3332 | 1.4101 | 1.1875 |
293
+ | No log | 10.5217 | 484 | 1.3472 | 0.3332 | 1.3472 | 1.1607 |
294
+ | No log | 10.5652 | 486 | 1.2700 | 0.2586 | 1.2700 | 1.1269 |
295
+ | No log | 10.6087 | 488 | 1.1424 | 0.2195 | 1.1424 | 1.0688 |
296
+ | No log | 10.6522 | 490 | 1.0848 | 0.1214 | 1.0848 | 1.0415 |
297
+ | No log | 10.6957 | 492 | 1.0346 | 0.1649 | 1.0346 | 1.0171 |
298
+ | No log | 10.7391 | 494 | 1.0200 | 0.1649 | 1.0200 | 1.0100 |
299
+ | No log | 10.7826 | 496 | 0.9957 | 0.1546 | 0.9957 | 0.9978 |
300
+ | No log | 10.8261 | 498 | 1.0261 | 0.1649 | 1.0261 | 1.0130 |
301
+ | 0.397 | 10.8696 | 500 | 1.1662 | 0.2051 | 1.1662 | 1.0799 |
302
+ | 0.397 | 10.9130 | 502 | 1.2600 | 0.2553 | 1.2600 | 1.1225 |
303
+ | 0.397 | 10.9565 | 504 | 1.2668 | 0.2553 | 1.2668 | 1.1255 |
304
+ | 0.397 | 11.0 | 506 | 1.3038 | 0.1789 | 1.3038 | 1.1418 |
305
+ | 0.397 | 11.0435 | 508 | 1.3706 | 0.1889 | 1.3706 | 1.1707 |
306
+ | 0.397 | 11.0870 | 510 | 1.3891 | 0.1889 | 1.3891 | 1.1786 |
307
+ | 0.397 | 11.1304 | 512 | 1.3745 | 0.1889 | 1.3745 | 1.1724 |
308
+ | 0.397 | 11.1739 | 514 | 1.3240 | 0.0887 | 1.3240 | 1.1507 |
309
+
310
+
311
+ ### Framework versions
312
+
313
+ - Transformers 4.44.2
314
+ - Pytorch 2.4.0+cu118
315
+ - Datasets 2.21.0
316
+ - Tokenizers 0.19.1
config.json ADDED
@@ -0,0 +1,32 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "_name_or_path": "aubmindlab/bert-base-arabertv02",
3
+ "architectures": [
4
+ "BertForSequenceClassification"
5
+ ],
6
+ "attention_probs_dropout_prob": 0.1,
7
+ "classifier_dropout": null,
8
+ "hidden_act": "gelu",
9
+ "hidden_dropout_prob": 0.1,
10
+ "hidden_size": 768,
11
+ "id2label": {
12
+ "0": "LABEL_0"
13
+ },
14
+ "initializer_range": 0.02,
15
+ "intermediate_size": 3072,
16
+ "label2id": {
17
+ "LABEL_0": 0
18
+ },
19
+ "layer_norm_eps": 1e-12,
20
+ "max_position_embeddings": 512,
21
+ "model_type": "bert",
22
+ "num_attention_heads": 12,
23
+ "num_hidden_layers": 12,
24
+ "pad_token_id": 0,
25
+ "position_embedding_type": "absolute",
26
+ "problem_type": "regression",
27
+ "torch_dtype": "float32",
28
+ "transformers_version": "4.44.2",
29
+ "type_vocab_size": 2,
30
+ "use_cache": true,
31
+ "vocab_size": 64000
32
+ }
model.safetensors ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:f8574cb850eac990845b37144ecd3f39ba4dbf7e7c46f5acc044f053418b90f4
3
+ size 540799996
training_args.bin ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:40c21394a7b612cbe716d1a209b6c5f302990f12b1e74f1c1e264ca6cbf93e6f
3
+ size 5304