Hugging Face's logo

MayBashendy
/
ArabicNewSplits7_B_usingALLEssays_FineTuningAraBERT_run1_AugV5_k3_task2_organization

Text Classification
Transformers
Safetensors
bert
Generated from Trainer
Model card Files
xet
 Community
MayBashendy commited on
Commit
e8f4277
·
verified ·
1 Parent(s): 897f9d0

Training in progress, step 500

Browse files
Files changed (4) hide show
  1. README.md +333 -0
  2. config.json +32 -0
  3. model.safetensors +3 -0
  4. training_args.bin +3 -0
README.md ADDED
@@ -0,0 +1,333 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ library_name: transformers
3
+ base_model: aubmindlab/bert-base-arabertv02
4
+ tags:
5
+ - generated_from_trainer
6
+ model-index:
7
+ - name: ArabicNewSplits7_B_usingALLEssays_FineTuningAraBERT_run1_AugV5_k2_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_B_usingALLEssays_FineTuningAraBERT_run1_AugV5_k2_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: 0.8427
19
+ - Qwk: 0.4734
20
+ - Mse: 0.8427
21
+ - Rmse: 0.9180
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 | 0.1538 | 2 | 4.7749 | -0.0132 | 4.7749 | 2.1852 |
53
+ | No log | 0.3077 | 4 | 3.2908 | 0.0080 | 3.2908 | 1.8140 |
54
+ | No log | 0.4615 | 6 | 1.7212 | 0.0504 | 1.7212 | 1.3119 |
55
+ | No log | 0.6154 | 8 | 1.8480 | 0.0062 | 1.8480 | 1.3594 |
56
+ | No log | 0.7692 | 10 | 1.7144 | -0.0809 | 1.7144 | 1.3093 |
57
+ | No log | 0.9231 | 12 | 1.3804 | 0.0639 | 1.3804 | 1.1749 |
58
+ | No log | 1.0769 | 14 | 1.1870 | 0.1570 | 1.1870 | 1.0895 |
59
+ | No log | 1.2308 | 16 | 1.1468 | 0.1875 | 1.1468 | 1.0709 |
60
+ | No log | 1.3846 | 18 | 1.1270 | 0.1918 | 1.1270 | 1.0616 |
61
+ | No log | 1.5385 | 20 | 1.1120 | 0.2674 | 1.1120 | 1.0545 |
62
+ | No log | 1.6923 | 22 | 1.0866 | 0.2887 | 1.0866 | 1.0424 |
63
+ | No log | 1.8462 | 24 | 1.1197 | 0.2785 | 1.1197 | 1.0582 |
64
+ | No log | 2.0 | 26 | 1.3853 | 0.1984 | 1.3853 | 1.1770 |
65
+ | No log | 2.1538 | 28 | 1.6560 | 0.1324 | 1.6560 | 1.2869 |
66
+ | No log | 2.3077 | 30 | 1.4621 | 0.1568 | 1.4621 | 1.2092 |
67
+ | No log | 2.4615 | 32 | 1.2327 | 0.1315 | 1.2327 | 1.1103 |
68
+ | No log | 2.6154 | 34 | 1.2224 | 0.2108 | 1.2224 | 1.1056 |
69
+ | No log | 2.7692 | 36 | 1.1513 | 0.2395 | 1.1513 | 1.0730 |
70
+ | No log | 2.9231 | 38 | 1.0896 | 0.3135 | 1.0896 | 1.0438 |
71
+ | No log | 3.0769 | 40 | 1.0795 | 0.3135 | 1.0795 | 1.0390 |
72
+ | No log | 3.2308 | 42 | 1.0705 | 0.3284 | 1.0705 | 1.0347 |
73
+ | No log | 3.3846 | 44 | 1.0948 | 0.2738 | 1.0948 | 1.0463 |
74
+ | No log | 3.5385 | 46 | 1.1099 | 0.2626 | 1.1099 | 1.0535 |
75
+ | No log | 3.6923 | 48 | 1.0611 | 0.2844 | 1.0611 | 1.0301 |
76
+ | No log | 3.8462 | 50 | 0.9345 | 0.4874 | 0.9345 | 0.9667 |
77
+ | No log | 4.0 | 52 | 0.9538 | 0.3908 | 0.9538 | 0.9766 |
78
+ | No log | 4.1538 | 54 | 0.9635 | 0.4013 | 0.9635 | 0.9816 |
79
+ | No log | 4.3077 | 56 | 0.9369 | 0.4749 | 0.9369 | 0.9680 |
80
+ | No log | 4.4615 | 58 | 1.0159 | 0.4119 | 1.0159 | 1.0079 |
81
+ | No log | 4.6154 | 60 | 1.1238 | 0.2398 | 1.1238 | 1.0601 |
82
+ | No log | 4.7692 | 62 | 1.1461 | 0.2529 | 1.1461 | 1.0706 |
83
+ | No log | 4.9231 | 64 | 0.9655 | 0.4392 | 0.9655 | 0.9826 |
84
+ | No log | 5.0769 | 66 | 0.8731 | 0.4488 | 0.8731 | 0.9344 |
85
+ | No log | 5.2308 | 68 | 0.9184 | 0.5042 | 0.9184 | 0.9583 |
86
+ | No log | 5.3846 | 70 | 0.8913 | 0.5365 | 0.8913 | 0.9441 |
87
+ | No log | 5.5385 | 72 | 0.8174 | 0.5241 | 0.8174 | 0.9041 |
88
+ | No log | 5.6923 | 74 | 0.9064 | 0.5082 | 0.9064 | 0.9521 |
89
+ | No log | 5.8462 | 76 | 0.8902 | 0.5190 | 0.8902 | 0.9435 |
90
+ | No log | 6.0 | 78 | 0.8087 | 0.5155 | 0.8087 | 0.8993 |
91
+ | No log | 6.1538 | 80 | 0.7735 | 0.5439 | 0.7735 | 0.8795 |
92
+ | No log | 6.3077 | 82 | 0.8143 | 0.5673 | 0.8143 | 0.9024 |
93
+ | No log | 6.4615 | 84 | 0.8548 | 0.5125 | 0.8548 | 0.9245 |
94
+ | No log | 6.6154 | 86 | 0.8685 | 0.5079 | 0.8685 | 0.9320 |
95
+ | No log | 6.7692 | 88 | 0.9189 | 0.4513 | 0.9189 | 0.9586 |
96
+ | No log | 6.9231 | 90 | 0.8865 | 0.4859 | 0.8865 | 0.9416 |
97
+ | No log | 7.0769 | 92 | 0.8970 | 0.4600 | 0.8970 | 0.9471 |
98
+ | No log | 7.2308 | 94 | 0.8160 | 0.5181 | 0.8160 | 0.9033 |
99
+ | No log | 7.3846 | 96 | 0.7784 | 0.4947 | 0.7784 | 0.8822 |
100
+ | No log | 7.5385 | 98 | 0.7675 | 0.5137 | 0.7675 | 0.8761 |
101
+ | No log | 7.6923 | 100 | 0.7761 | 0.5267 | 0.7761 | 0.8810 |
102
+ | No log | 7.8462 | 102 | 0.7900 | 0.5455 | 0.7900 | 0.8888 |
103
+ | No log | 8.0 | 104 | 0.8512 | 0.5578 | 0.8512 | 0.9226 |
104
+ | No log | 8.1538 | 106 | 0.9026 | 0.5614 | 0.9026 | 0.9501 |
105
+ | No log | 8.3077 | 108 | 0.8299 | 0.5501 | 0.8299 | 0.9110 |
106
+ | No log | 8.4615 | 110 | 0.8581 | 0.5192 | 0.8581 | 0.9263 |
107
+ | No log | 8.6154 | 112 | 0.8781 | 0.5211 | 0.8781 | 0.9370 |
108
+ | No log | 8.7692 | 114 | 0.8411 | 0.5947 | 0.8411 | 0.9171 |
109
+ | No log | 8.9231 | 116 | 1.1985 | 0.5256 | 1.1985 | 1.0948 |
110
+ | No log | 9.0769 | 118 | 1.3963 | 0.4212 | 1.3963 | 1.1817 |
111
+ | No log | 9.2308 | 120 | 1.1747 | 0.3630 | 1.1747 | 1.0839 |
112
+ | No log | 9.3846 | 122 | 0.9600 | 0.2850 | 0.9600 | 0.9798 |
113
+ | No log | 9.5385 | 124 | 0.8463 | 0.3804 | 0.8463 | 0.9200 |
114
+ | No log | 9.6923 | 126 | 0.7858 | 0.4760 | 0.7858 | 0.8864 |
115
+ | No log | 9.8462 | 128 | 0.7875 | 0.4872 | 0.7875 | 0.8874 |
116
+ | No log | 10.0 | 130 | 0.7983 | 0.5205 | 0.7983 | 0.8935 |
117
+ | No log | 10.1538 | 132 | 0.9088 | 0.5636 | 0.9088 | 0.9533 |
118
+ | No log | 10.3077 | 134 | 1.0216 | 0.4836 | 1.0216 | 1.0108 |
119
+ | No log | 10.4615 | 136 | 0.9023 | 0.5624 | 0.9023 | 0.9499 |
120
+ | No log | 10.6154 | 138 | 0.8161 | 0.5507 | 0.8161 | 0.9034 |
121
+ | No log | 10.7692 | 140 | 0.8219 | 0.5279 | 0.8219 | 0.9066 |
122
+ | No log | 10.9231 | 142 | 0.8273 | 0.5056 | 0.8273 | 0.9096 |
123
+ | No log | 11.0769 | 144 | 0.8498 | 0.4982 | 0.8498 | 0.9218 |
124
+ | No log | 11.2308 | 146 | 0.8679 | 0.4853 | 0.8679 | 0.9316 |
125
+ | No log | 11.3846 | 148 | 0.8756 | 0.4737 | 0.8756 | 0.9358 |
126
+ | No log | 11.5385 | 150 | 0.8798 | 0.4737 | 0.8798 | 0.9380 |
127
+ | No log | 11.6923 | 152 | 0.8554 | 0.4250 | 0.8554 | 0.9249 |
128
+ | No log | 11.8462 | 154 | 0.8556 | 0.4920 | 0.8556 | 0.9250 |
129
+ | No log | 12.0 | 156 | 0.8512 | 0.5149 | 0.8512 | 0.9226 |
130
+ | No log | 12.1538 | 158 | 0.8589 | 0.3870 | 0.8589 | 0.9268 |
131
+ | No log | 12.3077 | 160 | 0.8696 | 0.4716 | 0.8696 | 0.9325 |
132
+ | No log | 12.4615 | 162 | 0.8342 | 0.4757 | 0.8342 | 0.9134 |
133
+ | No log | 12.6154 | 164 | 0.8234 | 0.4847 | 0.8234 | 0.9074 |
134
+ | No log | 12.7692 | 166 | 0.8282 | 0.5022 | 0.8282 | 0.9101 |
135
+ | No log | 12.9231 | 168 | 0.8448 | 0.5611 | 0.8448 | 0.9191 |
136
+ | No log | 13.0769 | 170 | 1.0438 | 0.5384 | 1.0438 | 1.0216 |
137
+ | No log | 13.2308 | 172 | 1.0200 | 0.5384 | 1.0200 | 1.0100 |
138
+ | No log | 13.3846 | 174 | 0.8441 | 0.5587 | 0.8441 | 0.9188 |
139
+ | No log | 13.5385 | 176 | 0.8192 | 0.5159 | 0.8192 | 0.9051 |
140
+ | No log | 13.6923 | 178 | 0.8405 | 0.5024 | 0.8405 | 0.9168 |
141
+ | No log | 13.8462 | 180 | 0.8592 | 0.5147 | 0.8592 | 0.9269 |
142
+ | No log | 14.0 | 182 | 0.9036 | 0.4660 | 0.9036 | 0.9506 |
143
+ | No log | 14.1538 | 184 | 0.9849 | 0.5201 | 0.9849 | 0.9924 |
144
+ | No log | 14.3077 | 186 | 0.9611 | 0.5218 | 0.9611 | 0.9804 |
145
+ | No log | 14.4615 | 188 | 0.8829 | 0.4621 | 0.8829 | 0.9396 |
146
+ | No log | 14.6154 | 190 | 0.8550 | 0.5316 | 0.8550 | 0.9247 |
147
+ | No log | 14.7692 | 192 | 0.8993 | 0.5766 | 0.8993 | 0.9483 |
148
+ | No log | 14.9231 | 194 | 0.8348 | 0.5090 | 0.8348 | 0.9137 |
149
+ | No log | 15.0769 | 196 | 0.7918 | 0.5507 | 0.7918 | 0.8898 |
150
+ | No log | 15.2308 | 198 | 0.8673 | 0.4930 | 0.8673 | 0.9313 |
151
+ | No log | 15.3846 | 200 | 0.8919 | 0.4780 | 0.8919 | 0.9444 |
152
+ | No log | 15.5385 | 202 | 0.7824 | 0.5455 | 0.7824 | 0.8845 |
153
+ | No log | 15.6923 | 204 | 0.7562 | 0.5826 | 0.7562 | 0.8696 |
154
+ | No log | 15.8462 | 206 | 0.7543 | 0.5916 | 0.7543 | 0.8685 |
155
+ | No log | 16.0 | 208 | 0.7767 | 0.5359 | 0.7767 | 0.8813 |
156
+ | No log | 16.1538 | 210 | 0.8455 | 0.3986 | 0.8455 | 0.9195 |
157
+ | No log | 16.3077 | 212 | 0.9177 | 0.4874 | 0.9177 | 0.9579 |
158
+ | No log | 16.4615 | 214 | 0.9622 | 0.5241 | 0.9622 | 0.9809 |
159
+ | No log | 16.6154 | 216 | 0.8580 | 0.5385 | 0.8580 | 0.9263 |
160
+ | No log | 16.7692 | 218 | 0.8091 | 0.5455 | 0.8091 | 0.8995 |
161
+ | No log | 16.9231 | 220 | 0.8468 | 0.5737 | 0.8468 | 0.9202 |
162
+ | No log | 17.0769 | 222 | 0.8661 | 0.5468 | 0.8661 | 0.9306 |
163
+ | No log | 17.2308 | 224 | 0.8061 | 0.5833 | 0.8061 | 0.8979 |
164
+ | No log | 17.3846 | 226 | 0.8319 | 0.5411 | 0.8319 | 0.9121 |
165
+ | No log | 17.5385 | 228 | 0.8867 | 0.5041 | 0.8867 | 0.9416 |
166
+ | No log | 17.6923 | 230 | 0.8739 | 0.4663 | 0.8739 | 0.9348 |
167
+ | No log | 17.8462 | 232 | 0.8136 | 0.4505 | 0.8136 | 0.9020 |
168
+ | No log | 18.0 | 234 | 0.8096 | 0.4505 | 0.8096 | 0.8998 |
169
+ | No log | 18.1538 | 236 | 0.8089 | 0.4409 | 0.8089 | 0.8994 |
170
+ | No log | 18.3077 | 238 | 0.8260 | 0.5563 | 0.8260 | 0.9088 |
171
+ | No log | 18.4615 | 240 | 0.8751 | 0.4902 | 0.8751 | 0.9355 |
172
+ | No log | 18.6154 | 242 | 0.8722 | 0.5200 | 0.8722 | 0.9339 |
173
+ | No log | 18.7692 | 244 | 0.8443 | 0.5686 | 0.8443 | 0.9188 |
174
+ | No log | 18.9231 | 246 | 0.8310 | 0.5271 | 0.8310 | 0.9116 |
175
+ | No log | 19.0769 | 248 | 0.8511 | 0.5107 | 0.8511 | 0.9225 |
176
+ | No log | 19.2308 | 250 | 0.9941 | 0.4350 | 0.9941 | 0.9970 |
177
+ | No log | 19.3846 | 252 | 1.0937 | 0.4217 | 1.0937 | 1.0458 |
178
+ | No log | 19.5385 | 254 | 0.9544 | 0.4281 | 0.9544 | 0.9769 |
179
+ | No log | 19.6923 | 256 | 0.8565 | 0.4676 | 0.8565 | 0.9255 |
180
+ | No log | 19.8462 | 258 | 0.9592 | 0.5109 | 0.9592 | 0.9794 |
181
+ | No log | 20.0 | 260 | 1.0031 | 0.5328 | 1.0031 | 1.0015 |
182
+ | No log | 20.1538 | 262 | 0.9488 | 0.5276 | 0.9488 | 0.9741 |
183
+ | No log | 20.3077 | 264 | 0.8304 | 0.5086 | 0.8304 | 0.9113 |
184
+ | No log | 20.4615 | 266 | 0.7788 | 0.5607 | 0.7788 | 0.8825 |
185
+ | No log | 20.6154 | 268 | 0.7977 | 0.5859 | 0.7977 | 0.8931 |
186
+ | No log | 20.7692 | 270 | 0.7797 | 0.5632 | 0.7797 | 0.8830 |
187
+ | No log | 20.9231 | 272 | 0.7637 | 0.5732 | 0.7637 | 0.8739 |
188
+ | No log | 21.0769 | 274 | 0.7876 | 0.6089 | 0.7876 | 0.8874 |
189
+ | No log | 21.2308 | 276 | 0.8290 | 0.6334 | 0.8290 | 0.9105 |
190
+ | No log | 21.3846 | 278 | 0.7954 | 0.6131 | 0.7954 | 0.8919 |
191
+ | No log | 21.5385 | 280 | 0.7708 | 0.5607 | 0.7708 | 0.8779 |
192
+ | No log | 21.6923 | 282 | 0.7801 | 0.5320 | 0.7801 | 0.8832 |
193
+ | No log | 21.8462 | 284 | 0.7855 | 0.5348 | 0.7855 | 0.8863 |
194
+ | No log | 22.0 | 286 | 0.7705 | 0.5415 | 0.7705 | 0.8778 |
195
+ | No log | 22.1538 | 288 | 0.7623 | 0.5826 | 0.7623 | 0.8731 |
196
+ | No log | 22.3077 | 290 | 0.7630 | 0.5946 | 0.7630 | 0.8735 |
197
+ | No log | 22.4615 | 292 | 0.7672 | 0.5946 | 0.7672 | 0.8759 |
198
+ | No log | 22.6154 | 294 | 0.7790 | 0.5596 | 0.7790 | 0.8826 |
199
+ | No log | 22.7692 | 296 | 0.7766 | 0.5509 | 0.7766 | 0.8812 |
200
+ | No log | 22.9231 | 298 | 0.7900 | 0.5396 | 0.7900 | 0.8888 |
201
+ | No log | 23.0769 | 300 | 0.7855 | 0.5511 | 0.7855 | 0.8863 |
202
+ | No log | 23.2308 | 302 | 0.7823 | 0.5621 | 0.7823 | 0.8845 |
203
+ | No log | 23.3846 | 304 | 0.7911 | 0.5396 | 0.7911 | 0.8894 |
204
+ | No log | 23.5385 | 306 | 0.8191 | 0.5041 | 0.8191 | 0.9050 |
205
+ | No log | 23.6923 | 308 | 0.8667 | 0.4533 | 0.8667 | 0.9310 |
206
+ | No log | 23.8462 | 310 | 0.9270 | 0.4521 | 0.9270 | 0.9628 |
207
+ | No log | 24.0 | 312 | 0.9415 | 0.4515 | 0.9415 | 0.9703 |
208
+ | No log | 24.1538 | 314 | 0.9138 | 0.4515 | 0.9138 | 0.9559 |
209
+ | No log | 24.3077 | 316 | 0.8634 | 0.4359 | 0.8634 | 0.9292 |
210
+ | No log | 24.4615 | 318 | 0.8620 | 0.4110 | 0.8620 | 0.9285 |
211
+ | No log | 24.6154 | 320 | 0.8603 | 0.4110 | 0.8603 | 0.9275 |
212
+ | No log | 24.7692 | 322 | 0.8810 | 0.4110 | 0.8810 | 0.9386 |
213
+ | No log | 24.9231 | 324 | 0.8780 | 0.4110 | 0.8780 | 0.9370 |
214
+ | No log | 25.0769 | 326 | 0.8349 | 0.5650 | 0.8349 | 0.9137 |
215
+ | No log | 25.2308 | 328 | 0.8299 | 0.5061 | 0.8299 | 0.9110 |
216
+ | No log | 25.3846 | 330 | 0.8347 | 0.4534 | 0.8347 | 0.9136 |
217
+ | No log | 25.5385 | 332 | 0.8242 | 0.5061 | 0.8242 | 0.9078 |
218
+ | No log | 25.6923 | 334 | 0.8379 | 0.4961 | 0.8379 | 0.9154 |
219
+ | No log | 25.8462 | 336 | 0.8270 | 0.4483 | 0.8270 | 0.9094 |
220
+ | No log | 26.0 | 338 | 0.8185 | 0.4872 | 0.8185 | 0.9047 |
221
+ | No log | 26.1538 | 340 | 0.8114 | 0.5581 | 0.8114 | 0.9008 |
222
+ | No log | 26.3077 | 342 | 0.8188 | 0.5336 | 0.8188 | 0.9049 |
223
+ | No log | 26.4615 | 344 | 0.8240 | 0.5570 | 0.8240 | 0.9078 |
224
+ | No log | 26.6154 | 346 | 0.8209 | 0.5474 | 0.8209 | 0.9061 |
225
+ | No log | 26.7692 | 348 | 0.7959 | 0.5107 | 0.7959 | 0.8921 |
226
+ | No log | 26.9231 | 350 | 0.7841 | 0.5634 | 0.7841 | 0.8855 |
227
+ | No log | 27.0769 | 352 | 0.7949 | 0.5226 | 0.7949 | 0.8916 |
228
+ | No log | 27.2308 | 354 | 0.7818 | 0.5634 | 0.7818 | 0.8842 |
229
+ | No log | 27.3846 | 356 | 0.8156 | 0.5013 | 0.8156 | 0.9031 |
230
+ | No log | 27.5385 | 358 | 0.9265 | 0.4973 | 0.9265 | 0.9625 |
231
+ | No log | 27.6923 | 360 | 0.9506 | 0.4973 | 0.9506 | 0.9750 |
232
+ | No log | 27.8462 | 362 | 0.8736 | 0.4654 | 0.8736 | 0.9347 |
233
+ | No log | 28.0 | 364 | 0.8199 | 0.5622 | 0.8199 | 0.9055 |
234
+ | No log | 28.1538 | 366 | 0.8185 | 0.5622 | 0.8185 | 0.9047 |
235
+ | No log | 28.3077 | 368 | 0.8400 | 0.4808 | 0.8400 | 0.9165 |
236
+ | No log | 28.4615 | 370 | 0.8492 | 0.4808 | 0.8492 | 0.9215 |
237
+ | No log | 28.6154 | 372 | 0.8505 | 0.4459 | 0.8505 | 0.9222 |
238
+ | No log | 28.7692 | 374 | 0.8404 | 0.4459 | 0.8404 | 0.9167 |
239
+ | No log | 28.9231 | 376 | 0.8422 | 0.4714 | 0.8422 | 0.9177 |
240
+ | No log | 29.0769 | 378 | 0.8445 | 0.4714 | 0.8445 | 0.9190 |
241
+ | No log | 29.2308 | 380 | 0.8338 | 0.5426 | 0.8338 | 0.9131 |
242
+ | No log | 29.3846 | 382 | 0.8377 | 0.5155 | 0.8377 | 0.9152 |
243
+ | No log | 29.5385 | 384 | 0.8424 | 0.5155 | 0.8424 | 0.9178 |
244
+ | No log | 29.6923 | 386 | 0.8470 | 0.5155 | 0.8470 | 0.9203 |
245
+ | No log | 29.8462 | 388 | 0.8614 | 0.5245 | 0.8614 | 0.9281 |
246
+ | No log | 30.0 | 390 | 0.8610 | 0.5335 | 0.8610 | 0.9279 |
247
+ | No log | 30.1538 | 392 | 0.8551 | 0.5536 | 0.8551 | 0.9247 |
248
+ | No log | 30.3077 | 394 | 0.8499 | 0.4820 | 0.8499 | 0.9219 |
249
+ | No log | 30.4615 | 396 | 0.8491 | 0.4459 | 0.8491 | 0.9215 |
250
+ | No log | 30.6154 | 398 | 0.8410 | 0.4690 | 0.8410 | 0.9171 |
251
+ | No log | 30.7692 | 400 | 0.8481 | 0.4690 | 0.8481 | 0.9209 |
252
+ | No log | 30.9231 | 402 | 0.8638 | 0.4690 | 0.8638 | 0.9294 |
253
+ | No log | 31.0769 | 404 | 0.8423 | 0.4690 | 0.8423 | 0.9177 |
254
+ | No log | 31.2308 | 406 | 0.8274 | 0.4700 | 0.8274 | 0.9096 |
255
+ | No log | 31.3846 | 408 | 0.8229 | 0.5045 | 0.8229 | 0.9071 |
256
+ | No log | 31.5385 | 410 | 0.8413 | 0.4690 | 0.8413 | 0.9172 |
257
+ | No log | 31.6923 | 412 | 0.9187 | 0.4724 | 0.9187 | 0.9585 |
258
+ | No log | 31.8462 | 414 | 0.9727 | 0.4790 | 0.9727 | 0.9863 |
259
+ | No log | 32.0 | 416 | 0.9425 | 0.4404 | 0.9425 | 0.9708 |
260
+ | No log | 32.1538 | 418 | 0.8836 | 0.4454 | 0.8836 | 0.9400 |
261
+ | No log | 32.3077 | 420 | 0.8743 | 0.4700 | 0.8743 | 0.9351 |
262
+ | No log | 32.4615 | 422 | 0.8717 | 0.4142 | 0.8717 | 0.9337 |
263
+ | No log | 32.6154 | 424 | 0.8747 | 0.4142 | 0.8747 | 0.9352 |
264
+ | No log | 32.7692 | 426 | 0.8849 | 0.4700 | 0.8849 | 0.9407 |
265
+ | No log | 32.9231 | 428 | 0.9142 | 0.4331 | 0.9142 | 0.9561 |
266
+ | No log | 33.0769 | 430 | 0.9103 | 0.4331 | 0.9103 | 0.9541 |
267
+ | No log | 33.2308 | 432 | 0.8802 | 0.4700 | 0.8802 | 0.9382 |
268
+ | No log | 33.3846 | 434 | 0.8677 | 0.5192 | 0.8677 | 0.9315 |
269
+ | No log | 33.5385 | 436 | 0.8691 | 0.4690 | 0.8691 | 0.9322 |
270
+ | No log | 33.6923 | 438 | 0.8968 | 0.4459 | 0.8968 | 0.9470 |
271
+ | No log | 33.8462 | 440 | 0.9022 | 0.4237 | 0.9022 | 0.9499 |
272
+ | No log | 34.0 | 442 | 0.8791 | 0.4704 | 0.8791 | 0.9376 |
273
+ | No log | 34.1538 | 444 | 0.8730 | 0.5349 | 0.8730 | 0.9344 |
274
+ | No log | 34.3077 | 446 | 0.8799 | 0.5541 | 0.8799 | 0.9380 |
275
+ | No log | 34.4615 | 448 | 0.8696 | 0.5149 | 0.8696 | 0.9325 |
276
+ | No log | 34.6154 | 450 | 0.8673 | 0.5076 | 0.8673 | 0.9313 |
277
+ | No log | 34.7692 | 452 | 0.8781 | 0.4587 | 0.8781 | 0.9371 |
278
+ | No log | 34.9231 | 454 | 0.8760 | 0.4820 | 0.8760 | 0.9360 |
279
+ | No log | 35.0769 | 456 | 0.8638 | 0.5192 | 0.8638 | 0.9294 |
280
+ | No log | 35.2308 | 458 | 0.8660 | 0.5320 | 0.8660 | 0.9306 |
281
+ | No log | 35.3846 | 460 | 0.8667 | 0.5110 | 0.8667 | 0.9310 |
282
+ | No log | 35.5385 | 462 | 0.8575 | 0.4560 | 0.8575 | 0.9260 |
283
+ | No log | 35.6923 | 464 | 0.8981 | 0.4236 | 0.8981 | 0.9477 |
284
+ | No log | 35.8462 | 466 | 0.9624 | 0.4111 | 0.9624 | 0.9810 |
285
+ | No log | 36.0 | 468 | 0.9605 | 0.4111 | 0.9605 | 0.9801 |
286
+ | No log | 36.1538 | 470 | 0.9122 | 0.4110 | 0.9122 | 0.9551 |
287
+ | No log | 36.3077 | 472 | 0.8807 | 0.4241 | 0.8807 | 0.9384 |
288
+ | No log | 36.4615 | 474 | 0.8787 | 0.4217 | 0.8787 | 0.9374 |
289
+ | No log | 36.6154 | 476 | 0.8829 | 0.5208 | 0.8829 | 0.9396 |
290
+ | No log | 36.7692 | 478 | 0.8884 | 0.5500 | 0.8884 | 0.9426 |
291
+ | No log | 36.9231 | 480 | 0.8802 | 0.5426 | 0.8802 | 0.9382 |
292
+ | No log | 37.0769 | 482 | 0.8913 | 0.3977 | 0.8913 | 0.9441 |
293
+ | No log | 37.2308 | 484 | 0.9245 | 0.4113 | 0.9245 | 0.9615 |
294
+ | No log | 37.3846 | 486 | 0.9117 | 0.4113 | 0.9117 | 0.9549 |
295
+ | No log | 37.5385 | 488 | 0.8909 | 0.4110 | 0.8909 | 0.9439 |
296
+ | No log | 37.6923 | 490 | 0.8785 | 0.4690 | 0.8785 | 0.9373 |
297
+ | No log | 37.8462 | 492 | 0.8729 | 0.5173 | 0.8729 | 0.9343 |
298
+ | No log | 38.0 | 494 | 0.8732 | 0.5308 | 0.8732 | 0.9344 |
299
+ | No log | 38.1538 | 496 | 0.8763 | 0.5173 | 0.8763 | 0.9361 |
300
+ | No log | 38.3077 | 498 | 0.8812 | 0.4872 | 0.8812 | 0.9387 |
301
+ | 0.3079 | 38.4615 | 500 | 0.8831 | 0.4813 | 0.8831 | 0.9398 |
302
+ | 0.3079 | 38.6154 | 502 | 0.8847 | 0.5076 | 0.8847 | 0.9406 |
303
+ | 0.3079 | 38.7692 | 504 | 0.9036 | 0.4237 | 0.9036 | 0.9506 |
304
+ | 0.3079 | 38.9231 | 506 | 0.9428 | 0.3990 | 0.9428 | 0.9710 |
305
+ | 0.3079 | 39.0769 | 508 | 0.9374 | 0.3990 | 0.9374 | 0.9682 |
306
+ | 0.3079 | 39.2308 | 510 | 0.8961 | 0.4237 | 0.8961 | 0.9466 |
307
+ | 0.3079 | 39.3846 | 512 | 0.8639 | 0.5149 | 0.8639 | 0.9294 |
308
+ | 0.3079 | 39.5385 | 514 | 0.8826 | 0.5541 | 0.8826 | 0.9395 |
309
+ | 0.3079 | 39.6923 | 516 | 0.8867 | 0.5455 | 0.8867 | 0.9417 |
310
+ | 0.3079 | 39.8462 | 518 | 0.8593 | 0.5541 | 0.8593 | 0.9270 |
311
+ | 0.3079 | 40.0 | 520 | 0.8461 | 0.5555 | 0.8461 | 0.9198 |
312
+ | 0.3079 | 40.1538 | 522 | 0.8810 | 0.4237 | 0.8810 | 0.9386 |
313
+ | 0.3079 | 40.3077 | 524 | 0.9350 | 0.5294 | 0.9350 | 0.9669 |
314
+ | 0.3079 | 40.4615 | 526 | 0.9256 | 0.5294 | 0.9256 | 0.9621 |
315
+ | 0.3079 | 40.6154 | 528 | 0.8678 | 0.4672 | 0.8678 | 0.9315 |
316
+ | 0.3079 | 40.7692 | 530 | 0.8275 | 0.4884 | 0.8275 | 0.9097 |
317
+ | 0.3079 | 40.9231 | 532 | 0.8263 | 0.5415 | 0.8263 | 0.9090 |
318
+ | 0.3079 | 41.0769 | 534 | 0.8271 | 0.5538 | 0.8271 | 0.9094 |
319
+ | 0.3079 | 41.2308 | 536 | 0.8269 | 0.5233 | 0.8269 | 0.9094 |
320
+ | 0.3079 | 41.3846 | 538 | 0.8274 | 0.4980 | 0.8274 | 0.9096 |
321
+ | 0.3079 | 41.5385 | 540 | 0.8340 | 0.4499 | 0.8340 | 0.9132 |
322
+ | 0.3079 | 41.6923 | 542 | 0.8374 | 0.4493 | 0.8374 | 0.9151 |
323
+ | 0.3079 | 41.8462 | 544 | 0.8442 | 0.4587 | 0.8442 | 0.9188 |
324
+ | 0.3079 | 42.0 | 546 | 0.8376 | 0.4734 | 0.8376 | 0.9152 |
325
+ | 0.3079 | 42.1538 | 548 | 0.8427 | 0.4734 | 0.8427 | 0.9180 |
326
+
327
+
328
+ ### Framework versions
329
+
330
+ - Transformers 4.44.2
331
+ - Pytorch 2.4.0+cu118
332
+ - Datasets 2.21.0
333
+ - 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:c4d901545c068f3f3fc16c7fbede8105952b065e31539abf8db0c1aca56e3b91
3
+ size 540799996
training_args.bin ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:bde4ad0adc0838e017fec98ddc1c726ae8c0053ce9c695be1b6b55152a2de050
3
+ size 5304