Hugging Face's logo

MayBashendy
/
ArabicNewSplits7_usingALLEssays_FineTuningAraBERT_run2_AugV5_k10_task5_organization

Text Classification
Transformers
Safetensors
bert
Generated from Trainer
Model card Files
xet
 Community
MayBashendy commited on
Commit
ad6616e
·
verified ·
1 Parent(s): c6f8b1d

Training in progress, step 500

Browse files
Files changed (4) hide show
  1. README.md +314 -0
  2. config.json +32 -0
  3. model.safetensors +3 -0
  4. training_args.bin +3 -0
README.md ADDED
@@ -0,0 +1,314 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ library_name: transformers
3
+ base_model: aubmindlab/bert-base-arabertv02
4
+ tags:
5
+ - generated_from_trainer
6
+ model-index:
7
+ - name: ArabicNewSplits7_usingALLEssays_FineTuningAraBERT_run2_AugV5_k9_task5_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_usingALLEssays_FineTuningAraBERT_run2_AugV5_k9_task5_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: 0.9286
19
+ - Qwk: 0.3569
20
+ - Mse: 0.9286
21
+ - Rmse: 0.9636
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 | 0.0741 | 2 | 3.8713 | -0.0194 | 3.8713 | 1.9676 |
53
+ | No log | 0.1481 | 4 | 2.2402 | -0.0161 | 2.2402 | 1.4967 |
54
+ | No log | 0.2222 | 6 | 1.9907 | -0.0327 | 1.9907 | 1.4109 |
55
+ | No log | 0.2963 | 8 | 1.8715 | -0.0238 | 1.8715 | 1.3680 |
56
+ | No log | 0.3704 | 10 | 1.3279 | 0.1228 | 1.3279 | 1.1524 |
57
+ | No log | 0.4444 | 12 | 1.1018 | 0.2318 | 1.1018 | 1.0497 |
58
+ | No log | 0.5185 | 14 | 1.1949 | 0.0466 | 1.1949 | 1.0931 |
59
+ | No log | 0.5926 | 16 | 1.1864 | 0.1233 | 1.1864 | 1.0892 |
60
+ | No log | 0.6667 | 18 | 1.1256 | 0.2318 | 1.1256 | 1.0610 |
61
+ | No log | 0.7407 | 20 | 1.1697 | 0.1927 | 1.1697 | 1.0815 |
62
+ | No log | 0.8148 | 22 | 1.2302 | 0.0672 | 1.2302 | 1.1092 |
63
+ | No log | 0.8889 | 24 | 1.2700 | 0.0436 | 1.2700 | 1.1269 |
64
+ | No log | 0.9630 | 26 | 1.1554 | 0.1603 | 1.1554 | 1.0749 |
65
+ | No log | 1.0370 | 28 | 1.1203 | 0.1576 | 1.1203 | 1.0584 |
66
+ | No log | 1.1111 | 30 | 1.0943 | 0.2639 | 1.0943 | 1.0461 |
67
+ | No log | 1.1852 | 32 | 1.1171 | 0.1537 | 1.1171 | 1.0569 |
68
+ | No log | 1.2593 | 34 | 1.1267 | 0.1028 | 1.1267 | 1.0615 |
69
+ | No log | 1.3333 | 36 | 1.2231 | 0.1176 | 1.2231 | 1.1060 |
70
+ | No log | 1.4074 | 38 | 1.2779 | 0.1460 | 1.2779 | 1.1304 |
71
+ | No log | 1.4815 | 40 | 1.3606 | 0.1112 | 1.3606 | 1.1664 |
72
+ | No log | 1.5556 | 42 | 1.3127 | 0.1886 | 1.3127 | 1.1457 |
73
+ | No log | 1.6296 | 44 | 1.2353 | 0.1173 | 1.2353 | 1.1114 |
74
+ | No log | 1.7037 | 46 | 1.2003 | 0.1173 | 1.2003 | 1.0956 |
75
+ | No log | 1.7778 | 48 | 1.0856 | 0.1927 | 1.0856 | 1.0419 |
76
+ | No log | 1.8519 | 50 | 1.0854 | 0.1416 | 1.0854 | 1.0418 |
77
+ | No log | 1.9259 | 52 | 1.0831 | 0.1416 | 1.0831 | 1.0407 |
78
+ | No log | 2.0 | 54 | 1.0875 | 0.1779 | 1.0875 | 1.0428 |
79
+ | No log | 2.0741 | 56 | 1.1358 | 0.1389 | 1.1358 | 1.0657 |
80
+ | No log | 2.1481 | 58 | 1.2357 | 0.1482 | 1.2357 | 1.1116 |
81
+ | No log | 2.2222 | 60 | 1.3853 | -0.0548 | 1.3853 | 1.1770 |
82
+ | No log | 2.2963 | 62 | 1.4401 | -0.0342 | 1.4401 | 1.2001 |
83
+ | No log | 2.3704 | 64 | 1.1410 | 0.0914 | 1.1410 | 1.0682 |
84
+ | No log | 2.4444 | 66 | 1.0001 | 0.2183 | 1.0001 | 1.0000 |
85
+ | No log | 2.5185 | 68 | 1.2159 | 0.2644 | 1.2159 | 1.1027 |
86
+ | No log | 2.5926 | 70 | 1.4546 | 0.1998 | 1.4546 | 1.2061 |
87
+ | No log | 2.6667 | 72 | 1.3405 | 0.1387 | 1.3405 | 1.1578 |
88
+ | No log | 2.7407 | 74 | 1.1067 | 0.1927 | 1.1067 | 1.0520 |
89
+ | No log | 2.8148 | 76 | 0.9606 | 0.2782 | 0.9606 | 0.9801 |
90
+ | No log | 2.8889 | 78 | 0.9801 | 0.1918 | 0.9801 | 0.9900 |
91
+ | No log | 2.9630 | 80 | 1.0417 | 0.2192 | 1.0417 | 1.0207 |
92
+ | No log | 3.0370 | 82 | 1.1045 | 0.1671 | 1.1045 | 1.0509 |
93
+ | No log | 3.1111 | 84 | 1.0592 | 0.2549 | 1.0592 | 1.0292 |
94
+ | No log | 3.1852 | 86 | 0.9969 | 0.2175 | 0.9969 | 0.9985 |
95
+ | No log | 3.2593 | 88 | 0.9633 | 0.2850 | 0.9633 | 0.9815 |
96
+ | No log | 3.3333 | 90 | 0.9256 | 0.3020 | 0.9256 | 0.9621 |
97
+ | No log | 3.4074 | 92 | 0.9083 | 0.4269 | 0.9083 | 0.9530 |
98
+ | No log | 3.4815 | 94 | 0.9564 | 0.3747 | 0.9564 | 0.9779 |
99
+ | No log | 3.5556 | 96 | 1.0921 | 0.3577 | 1.0921 | 1.0450 |
100
+ | No log | 3.6296 | 98 | 1.1997 | 0.1009 | 1.1997 | 1.0953 |
101
+ | No log | 3.7037 | 100 | 1.5447 | 0.0122 | 1.5447 | 1.2428 |
102
+ | No log | 3.7778 | 102 | 1.7245 | 0.0293 | 1.7245 | 1.3132 |
103
+ | No log | 3.8519 | 104 | 1.4130 | 0.0955 | 1.4130 | 1.1887 |
104
+ | No log | 3.9259 | 106 | 1.0454 | 0.1841 | 1.0454 | 1.0224 |
105
+ | No log | 4.0 | 108 | 1.0472 | 0.3200 | 1.0472 | 1.0233 |
106
+ | No log | 4.0741 | 110 | 1.0214 | 0.3798 | 1.0214 | 1.0106 |
107
+ | No log | 4.1481 | 112 | 0.8998 | 0.3775 | 0.8998 | 0.9486 |
108
+ | No log | 4.2222 | 114 | 0.9100 | 0.4474 | 0.9100 | 0.9539 |
109
+ | No log | 4.2963 | 116 | 0.9062 | 0.4709 | 0.9062 | 0.9519 |
110
+ | No log | 4.3704 | 118 | 0.8424 | 0.4789 | 0.8424 | 0.9178 |
111
+ | No log | 4.4444 | 120 | 0.8557 | 0.4789 | 0.8557 | 0.9250 |
112
+ | No log | 4.5185 | 122 | 0.9407 | 0.4507 | 0.9407 | 0.9699 |
113
+ | No log | 4.5926 | 124 | 0.9148 | 0.4635 | 0.9148 | 0.9565 |
114
+ | No log | 4.6667 | 126 | 0.8392 | 0.5142 | 0.8392 | 0.9161 |
115
+ | No log | 4.7407 | 128 | 0.8353 | 0.5121 | 0.8353 | 0.9139 |
116
+ | No log | 4.8148 | 130 | 0.8498 | 0.4027 | 0.8498 | 0.9219 |
117
+ | No log | 4.8889 | 132 | 0.9020 | 0.3483 | 0.9020 | 0.9497 |
118
+ | No log | 4.9630 | 134 | 1.0153 | 0.3243 | 1.0153 | 1.0076 |
119
+ | No log | 5.0370 | 136 | 1.0757 | 0.3115 | 1.0757 | 1.0371 |
120
+ | No log | 5.1111 | 138 | 0.9743 | 0.3735 | 0.9743 | 0.9871 |
121
+ | No log | 5.1852 | 140 | 0.8840 | 0.4012 | 0.8840 | 0.9402 |
122
+ | No log | 5.2593 | 142 | 0.9192 | 0.3644 | 0.9192 | 0.9588 |
123
+ | No log | 5.3333 | 144 | 0.9911 | 0.3243 | 0.9911 | 0.9956 |
124
+ | No log | 5.4074 | 146 | 0.9397 | 0.3596 | 0.9397 | 0.9694 |
125
+ | No log | 5.4815 | 148 | 0.9045 | 0.4030 | 0.9045 | 0.9511 |
126
+ | No log | 5.5556 | 150 | 0.9131 | 0.3496 | 0.9131 | 0.9556 |
127
+ | No log | 5.6296 | 152 | 0.9409 | 0.3858 | 0.9409 | 0.9700 |
128
+ | No log | 5.7037 | 154 | 0.9459 | 0.3858 | 0.9459 | 0.9726 |
129
+ | No log | 5.7778 | 156 | 0.9592 | 0.3717 | 0.9592 | 0.9794 |
130
+ | No log | 5.8519 | 158 | 0.9558 | 0.3744 | 0.9558 | 0.9776 |
131
+ | No log | 5.9259 | 160 | 0.9944 | 0.3897 | 0.9944 | 0.9972 |
132
+ | No log | 6.0 | 162 | 1.1267 | 0.3601 | 1.1267 | 1.0615 |
133
+ | No log | 6.0741 | 164 | 1.1380 | 0.3715 | 1.1380 | 1.0668 |
134
+ | No log | 6.1481 | 166 | 0.9674 | 0.3418 | 0.9674 | 0.9836 |
135
+ | No log | 6.2222 | 168 | 0.9234 | 0.3610 | 0.9234 | 0.9609 |
136
+ | No log | 6.2963 | 170 | 0.9212 | 0.3610 | 0.9212 | 0.9598 |
137
+ | No log | 6.3704 | 172 | 0.9590 | 0.3992 | 0.9590 | 0.9793 |
138
+ | No log | 6.4444 | 174 | 1.0055 | 0.3217 | 1.0055 | 1.0027 |
139
+ | No log | 6.5185 | 176 | 0.9584 | 0.3959 | 0.9584 | 0.9790 |
140
+ | No log | 6.5926 | 178 | 0.9308 | 0.3367 | 0.9308 | 0.9648 |
141
+ | No log | 6.6667 | 180 | 0.9277 | 0.3878 | 0.9277 | 0.9632 |
142
+ | No log | 6.7407 | 182 | 0.9910 | 0.3483 | 0.9910 | 0.9955 |
143
+ | No log | 6.8148 | 184 | 1.1191 | 0.3929 | 1.1191 | 1.0579 |
144
+ | No log | 6.8889 | 186 | 1.1504 | 0.3261 | 1.1504 | 1.0725 |
145
+ | No log | 6.9630 | 188 | 1.0478 | 0.3083 | 1.0478 | 1.0236 |
146
+ | No log | 7.0370 | 190 | 0.9535 | 0.3536 | 0.9535 | 0.9765 |
147
+ | No log | 7.1111 | 192 | 0.9313 | 0.3382 | 0.9313 | 0.9650 |
148
+ | No log | 7.1852 | 194 | 0.9224 | 0.3536 | 0.9224 | 0.9604 |
149
+ | No log | 7.2593 | 196 | 0.9806 | 0.4259 | 0.9806 | 0.9902 |
150
+ | No log | 7.3333 | 198 | 1.0115 | 0.4268 | 1.0115 | 1.0057 |
151
+ | No log | 7.4074 | 200 | 0.9749 | 0.4268 | 0.9749 | 0.9874 |
152
+ | No log | 7.4815 | 202 | 0.9585 | 0.4020 | 0.9585 | 0.9790 |
153
+ | No log | 7.5556 | 204 | 1.0496 | 0.4032 | 1.0496 | 1.0245 |
154
+ | No log | 7.6296 | 206 | 1.0088 | 0.3792 | 1.0088 | 1.0044 |
155
+ | No log | 7.7037 | 208 | 0.8989 | 0.3506 | 0.8989 | 0.9481 |
156
+ | No log | 7.7778 | 210 | 0.8778 | 0.3112 | 0.8778 | 0.9369 |
157
+ | No log | 7.8519 | 212 | 0.8963 | 0.3922 | 0.8963 | 0.9467 |
158
+ | No log | 7.9259 | 214 | 0.9172 | 0.4020 | 0.9172 | 0.9577 |
159
+ | No log | 8.0 | 216 | 0.8824 | 0.4123 | 0.8824 | 0.9393 |
160
+ | No log | 8.0741 | 218 | 0.9084 | 0.4597 | 0.9084 | 0.9531 |
161
+ | No log | 8.1481 | 220 | 0.9135 | 0.4078 | 0.9135 | 0.9558 |
162
+ | No log | 8.2222 | 222 | 0.9133 | 0.4078 | 0.9133 | 0.9557 |
163
+ | No log | 8.2963 | 224 | 0.9236 | 0.4078 | 0.9236 | 0.9610 |
164
+ | No log | 8.3704 | 226 | 0.8893 | 0.4078 | 0.8893 | 0.9431 |
165
+ | No log | 8.4444 | 228 | 0.8905 | 0.4078 | 0.8905 | 0.9437 |
166
+ | No log | 8.5185 | 230 | 0.9283 | 0.4220 | 0.9283 | 0.9635 |
167
+ | No log | 8.5926 | 232 | 1.1043 | 0.3622 | 1.1043 | 1.0509 |
168
+ | No log | 8.6667 | 234 | 1.1794 | 0.3490 | 1.1794 | 1.0860 |
169
+ | No log | 8.7407 | 236 | 1.0679 | 0.3913 | 1.0679 | 1.0334 |
170
+ | No log | 8.8148 | 238 | 0.9385 | 0.3583 | 0.9385 | 0.9688 |
171
+ | No log | 8.8889 | 240 | 0.9111 | 0.2888 | 0.9111 | 0.9545 |
172
+ | No log | 8.9630 | 242 | 0.9150 | 0.2888 | 0.9150 | 0.9566 |
173
+ | No log | 9.0370 | 244 | 0.9471 | 0.3382 | 0.9471 | 0.9732 |
174
+ | No log | 9.1111 | 246 | 0.9761 | 0.3799 | 0.9761 | 0.9880 |
175
+ | No log | 9.1852 | 248 | 1.0135 | 0.3802 | 1.0135 | 1.0067 |
176
+ | No log | 9.2593 | 250 | 1.0330 | 0.3264 | 1.0330 | 1.0164 |
177
+ | No log | 9.3333 | 252 | 0.9740 | 0.2988 | 0.9740 | 0.9869 |
178
+ | No log | 9.4074 | 254 | 0.9596 | 0.2865 | 0.9596 | 0.9796 |
179
+ | No log | 9.4815 | 256 | 0.9662 | 0.2988 | 0.9662 | 0.9829 |
180
+ | No log | 9.5556 | 258 | 1.0169 | 0.3424 | 1.0169 | 1.0084 |
181
+ | No log | 9.6296 | 260 | 1.0461 | 0.3682 | 1.0461 | 1.0228 |
182
+ | No log | 9.7037 | 262 | 1.0059 | 0.3678 | 1.0059 | 1.0029 |
183
+ | No log | 9.7778 | 264 | 1.0027 | 0.2988 | 1.0027 | 1.0014 |
184
+ | No log | 9.8519 | 266 | 1.1058 | 0.2820 | 1.1058 | 1.0516 |
185
+ | No log | 9.9259 | 268 | 1.2064 | 0.1960 | 1.2064 | 1.0984 |
186
+ | No log | 10.0 | 270 | 1.1614 | 0.2416 | 1.1614 | 1.0777 |
187
+ | No log | 10.0741 | 272 | 1.0705 | 0.2963 | 1.0705 | 1.0347 |
188
+ | No log | 10.1481 | 274 | 0.9657 | 0.3011 | 0.9657 | 0.9827 |
189
+ | No log | 10.2222 | 276 | 0.9399 | 0.3014 | 0.9399 | 0.9695 |
190
+ | No log | 10.2963 | 278 | 0.9350 | 0.3014 | 0.9350 | 0.9670 |
191
+ | No log | 10.3704 | 280 | 0.9691 | 0.3112 | 0.9691 | 0.9844 |
192
+ | No log | 10.4444 | 282 | 1.0783 | 0.3222 | 1.0783 | 1.0384 |
193
+ | No log | 10.5185 | 284 | 1.1001 | 0.2091 | 1.1001 | 1.0489 |
194
+ | No log | 10.5926 | 286 | 1.0516 | 0.3207 | 1.0516 | 1.0255 |
195
+ | No log | 10.6667 | 288 | 0.9880 | 0.3757 | 0.9880 | 0.9940 |
196
+ | No log | 10.7407 | 290 | 0.9353 | 0.3094 | 0.9353 | 0.9671 |
197
+ | No log | 10.8148 | 292 | 0.9089 | 0.3243 | 0.9089 | 0.9534 |
198
+ | No log | 10.8889 | 294 | 0.9233 | 0.4063 | 0.9233 | 0.9609 |
199
+ | No log | 10.9630 | 296 | 0.9892 | 0.4439 | 0.9892 | 0.9946 |
200
+ | No log | 11.0370 | 298 | 0.9850 | 0.4310 | 0.9850 | 0.9925 |
201
+ | No log | 11.1111 | 300 | 0.9048 | 0.3922 | 0.9048 | 0.9512 |
202
+ | No log | 11.1852 | 302 | 0.8447 | 0.3693 | 0.8447 | 0.9191 |
203
+ | No log | 11.2593 | 304 | 0.8379 | 0.3569 | 0.8379 | 0.9154 |
204
+ | No log | 11.3333 | 306 | 0.8379 | 0.3858 | 0.8379 | 0.9154 |
205
+ | No log | 11.4074 | 308 | 0.8547 | 0.4101 | 0.8547 | 0.9245 |
206
+ | No log | 11.4815 | 310 | 0.9076 | 0.4487 | 0.9076 | 0.9527 |
207
+ | No log | 11.5556 | 312 | 0.9403 | 0.4499 | 0.9403 | 0.9697 |
208
+ | No log | 11.6296 | 314 | 0.9163 | 0.3765 | 0.9163 | 0.9572 |
209
+ | No log | 11.7037 | 316 | 0.9078 | 0.3569 | 0.9078 | 0.9528 |
210
+ | No log | 11.7778 | 318 | 0.9393 | 0.3548 | 0.9393 | 0.9692 |
211
+ | No log | 11.8519 | 320 | 0.9974 | 0.3611 | 0.9974 | 0.9987 |
212
+ | No log | 11.9259 | 322 | 1.0061 | 0.3611 | 1.0061 | 1.0031 |
213
+ | No log | 12.0 | 324 | 0.9997 | 0.3463 | 0.9997 | 0.9998 |
214
+ | No log | 12.0741 | 326 | 0.9584 | 0.3435 | 0.9584 | 0.9790 |
215
+ | No log | 12.1481 | 328 | 0.9449 | 0.3576 | 0.9449 | 0.9721 |
216
+ | No log | 12.2222 | 330 | 0.9856 | 0.3179 | 0.9856 | 0.9928 |
217
+ | No log | 12.2963 | 332 | 0.9665 | 0.3721 | 0.9665 | 0.9831 |
218
+ | No log | 12.3704 | 334 | 0.9504 | 0.3838 | 0.9504 | 0.9749 |
219
+ | No log | 12.4444 | 336 | 0.9586 | 0.3721 | 0.9586 | 0.9791 |
220
+ | No log | 12.5185 | 338 | 0.9637 | 0.3556 | 0.9637 | 0.9817 |
221
+ | No log | 12.5926 | 340 | 0.9285 | 0.3569 | 0.9285 | 0.9636 |
222
+ | No log | 12.6667 | 342 | 0.9119 | 0.3266 | 0.9119 | 0.9549 |
223
+ | No log | 12.7407 | 344 | 0.9129 | 0.3569 | 0.9129 | 0.9555 |
224
+ | No log | 12.8148 | 346 | 0.9512 | 0.3697 | 0.9512 | 0.9753 |
225
+ | No log | 12.8889 | 348 | 0.9906 | 0.2791 | 0.9906 | 0.9953 |
226
+ | No log | 12.9630 | 350 | 0.9986 | 0.2791 | 0.9986 | 0.9993 |
227
+ | No log | 13.0370 | 352 | 1.0823 | 0.3668 | 1.0823 | 1.0403 |
228
+ | No log | 13.1111 | 354 | 1.1154 | 0.3531 | 1.1154 | 1.0561 |
229
+ | No log | 13.1852 | 356 | 1.1069 | 0.3103 | 1.1069 | 1.0521 |
230
+ | No log | 13.2593 | 358 | 1.0788 | 0.2819 | 1.0788 | 1.0387 |
231
+ | No log | 13.3333 | 360 | 1.0221 | 0.1810 | 1.0221 | 1.0110 |
232
+ | No log | 13.4074 | 362 | 0.9828 | 0.3139 | 0.9828 | 0.9914 |
233
+ | No log | 13.4815 | 364 | 1.0007 | 0.2888 | 1.0007 | 1.0003 |
234
+ | No log | 13.5556 | 366 | 0.9963 | 0.2888 | 0.9963 | 0.9981 |
235
+ | No log | 13.6296 | 368 | 0.9977 | 0.2692 | 0.9977 | 0.9989 |
236
+ | No log | 13.7037 | 370 | 1.0037 | 0.2547 | 1.0037 | 1.0019 |
237
+ | No log | 13.7778 | 372 | 0.9938 | 0.3107 | 0.9938 | 0.9969 |
238
+ | No log | 13.8519 | 374 | 0.9714 | 0.3838 | 0.9714 | 0.9856 |
239
+ | No log | 13.9259 | 376 | 0.9370 | 0.3139 | 0.9370 | 0.9680 |
240
+ | No log | 14.0 | 378 | 0.9305 | 0.3139 | 0.9305 | 0.9646 |
241
+ | No log | 14.0741 | 380 | 0.9367 | 0.3596 | 0.9367 | 0.9678 |
242
+ | No log | 14.1481 | 382 | 0.9774 | 0.3658 | 0.9774 | 0.9887 |
243
+ | No log | 14.2222 | 384 | 1.0223 | 0.3782 | 1.0223 | 1.0111 |
244
+ | No log | 14.2963 | 386 | 1.0554 | 0.4283 | 1.0554 | 1.0273 |
245
+ | No log | 14.3704 | 388 | 1.0705 | 0.3483 | 1.0705 | 1.0346 |
246
+ | No log | 14.4444 | 390 | 1.0194 | 0.3351 | 1.0194 | 1.0097 |
247
+ | No log | 14.5185 | 392 | 0.9929 | 0.3393 | 0.9929 | 0.9965 |
248
+ | No log | 14.5926 | 394 | 0.9772 | 0.3536 | 0.9772 | 0.9885 |
249
+ | No log | 14.6667 | 396 | 0.9915 | 0.3393 | 0.9915 | 0.9957 |
250
+ | No log | 14.7407 | 398 | 1.0151 | 0.3494 | 1.0151 | 1.0075 |
251
+ | No log | 14.8148 | 400 | 1.0109 | 0.3351 | 1.0109 | 1.0054 |
252
+ | No log | 14.8889 | 402 | 0.9860 | 0.3044 | 0.9860 | 0.9930 |
253
+ | No log | 14.9630 | 404 | 0.9564 | 0.2942 | 0.9564 | 0.9780 |
254
+ | No log | 15.0370 | 406 | 0.9132 | 0.3819 | 0.9132 | 0.9556 |
255
+ | No log | 15.1111 | 408 | 0.8953 | 0.4371 | 0.8953 | 0.9462 |
256
+ | No log | 15.1852 | 410 | 0.8899 | 0.4115 | 0.8899 | 0.9433 |
257
+ | No log | 15.2593 | 412 | 0.8812 | 0.3996 | 0.8812 | 0.9387 |
258
+ | No log | 15.3333 | 414 | 0.8816 | 0.3323 | 0.8816 | 0.9389 |
259
+ | No log | 15.4074 | 416 | 0.8894 | 0.3014 | 0.8894 | 0.9431 |
260
+ | No log | 15.4815 | 418 | 0.8971 | 0.3014 | 0.8971 | 0.9471 |
261
+ | No log | 15.5556 | 420 | 0.8921 | 0.3569 | 0.8921 | 0.9445 |
262
+ | No log | 15.6296 | 422 | 0.8852 | 0.4133 | 0.8852 | 0.9409 |
263
+ | No log | 15.7037 | 424 | 0.8809 | 0.4251 | 0.8809 | 0.9386 |
264
+ | No log | 15.7778 | 426 | 0.9297 | 0.4476 | 0.9297 | 0.9642 |
265
+ | No log | 15.8519 | 428 | 1.0703 | 0.4043 | 1.0703 | 1.0345 |
266
+ | No log | 15.9259 | 430 | 1.2482 | 0.2599 | 1.2482 | 1.1172 |
267
+ | No log | 16.0 | 432 | 1.2722 | 0.2334 | 1.2722 | 1.1279 |
268
+ | No log | 16.0741 | 434 | 1.2258 | 0.0649 | 1.2258 | 1.1072 |
269
+ | No log | 16.1481 | 436 | 1.0952 | 0.2499 | 1.0952 | 1.0465 |
270
+ | No log | 16.2222 | 438 | 0.9734 | 0.2919 | 0.9734 | 0.9866 |
271
+ | No log | 16.2963 | 440 | 0.9180 | 0.4067 | 0.9180 | 0.9581 |
272
+ | No log | 16.3704 | 442 | 0.9105 | 0.3817 | 0.9105 | 0.9542 |
273
+ | No log | 16.4444 | 444 | 0.9328 | 0.4345 | 0.9328 | 0.9658 |
274
+ | No log | 16.5185 | 446 | 0.9731 | 0.4576 | 0.9731 | 0.9865 |
275
+ | No log | 16.5926 | 448 | 1.0351 | 0.3187 | 1.0351 | 1.0174 |
276
+ | No log | 16.6667 | 450 | 1.0426 | 0.3369 | 1.0426 | 1.0211 |
277
+ | No log | 16.7407 | 452 | 1.0052 | 0.4357 | 1.0052 | 1.0026 |
278
+ | No log | 16.8148 | 454 | 0.9584 | 0.4345 | 0.9584 | 0.9790 |
279
+ | No log | 16.8889 | 456 | 0.9499 | 0.3673 | 0.9499 | 0.9746 |
280
+ | No log | 16.9630 | 458 | 0.9666 | 0.4345 | 0.9666 | 0.9832 |
281
+ | No log | 17.0370 | 460 | 1.0123 | 0.3637 | 1.0123 | 1.0061 |
282
+ | No log | 17.1111 | 462 | 1.0434 | 0.3085 | 1.0434 | 1.0215 |
283
+ | No log | 17.1852 | 464 | 1.0161 | 0.3494 | 1.0161 | 1.0080 |
284
+ | No log | 17.2593 | 466 | 0.9604 | 0.3326 | 0.9604 | 0.9800 |
285
+ | No log | 17.3333 | 468 | 0.9551 | 0.3370 | 0.9551 | 0.9773 |
286
+ | No log | 17.4074 | 470 | 0.9574 | 0.3266 | 0.9574 | 0.9785 |
287
+ | No log | 17.4815 | 472 | 0.9752 | 0.3498 | 0.9752 | 0.9875 |
288
+ | No log | 17.5556 | 474 | 0.9789 | 0.3094 | 0.9789 | 0.9894 |
289
+ | No log | 17.6296 | 476 | 0.9772 | 0.3403 | 0.9772 | 0.9885 |
290
+ | No log | 17.7037 | 478 | 0.9939 | 0.3652 | 0.9939 | 0.9970 |
291
+ | No log | 17.7778 | 480 | 1.0174 | 0.3974 | 1.0174 | 1.0086 |
292
+ | No log | 17.8519 | 482 | 1.0252 | 0.3861 | 1.0252 | 1.0125 |
293
+ | No log | 17.9259 | 484 | 0.9811 | 0.3563 | 0.9811 | 0.9905 |
294
+ | No log | 18.0 | 486 | 0.9374 | 0.3569 | 0.9374 | 0.9682 |
295
+ | No log | 18.0741 | 488 | 0.9564 | 0.2912 | 0.9564 | 0.9780 |
296
+ | No log | 18.1481 | 490 | 0.9953 | 0.2687 | 0.9953 | 0.9977 |
297
+ | No log | 18.2222 | 492 | 0.9703 | 0.2811 | 0.9703 | 0.9850 |
298
+ | No log | 18.2963 | 494 | 0.9355 | 0.3590 | 0.9355 | 0.9672 |
299
+ | No log | 18.3704 | 496 | 0.9378 | 0.3596 | 0.9378 | 0.9684 |
300
+ | No log | 18.4444 | 498 | 0.9439 | 0.3622 | 0.9439 | 0.9716 |
301
+ | 0.2419 | 18.5185 | 500 | 0.9457 | 0.3642 | 0.9457 | 0.9725 |
302
+ | 0.2419 | 18.5926 | 502 | 0.9465 | 0.3642 | 0.9465 | 0.9729 |
303
+ | 0.2419 | 18.6667 | 504 | 0.9375 | 0.3642 | 0.9375 | 0.9683 |
304
+ | 0.2419 | 18.7407 | 506 | 0.9346 | 0.3622 | 0.9346 | 0.9667 |
305
+ | 0.2419 | 18.8148 | 508 | 0.9332 | 0.3596 | 0.9332 | 0.9660 |
306
+ | 0.2419 | 18.8889 | 510 | 0.9286 | 0.3569 | 0.9286 | 0.9636 |
307
+
308
+
309
+ ### Framework versions
310
+
311
+ - Transformers 4.44.2
312
+ - Pytorch 2.4.0+cu118
313
+ - Datasets 2.21.0
314
+ - 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:ed1b776dc9d559ff572603d1a2a05ce1bfe0d86ed4ec89d7c515bb0d95403973
3
+ size 540799996
training_args.bin ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:a35008077cb9bad855aed474ebf0cb58560bd7eaefa06b581fd053905fea4d90
3
+ size 5304