MayBashendy commited on
Commit
7f7ae50
·
verified ·
1 Parent(s): a0b203e

Training in progress, step 500

Browse files
Files changed (4) hide show
  1. README.md +327 -0
  2. config.json +32 -0
  3. model.safetensors +3 -0
  4. training_args.bin +3 -0
README.md ADDED
@@ -0,0 +1,327 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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_usingWellWrittenEssays_FineTuningAraBERT_run2_AugV5_k13_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_usingWellWrittenEssays_FineTuningAraBERT_run2_AugV5_k13_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: 0.8956
19
+ - Qwk: 0.3243
20
+ - Mse: 0.8956
21
+ - Rmse: 0.9464
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 | 0.0290 | 2 | 4.7607 | 0.0010 | 4.7607 | 2.1819 |
53
+ | No log | 0.0580 | 4 | 2.8285 | -0.0140 | 2.8285 | 1.6818 |
54
+ | No log | 0.0870 | 6 | 2.4053 | -0.0586 | 2.4053 | 1.5509 |
55
+ | No log | 0.1159 | 8 | 2.0279 | -0.0233 | 2.0279 | 1.4241 |
56
+ | No log | 0.1449 | 10 | 1.2468 | 0.1113 | 1.2468 | 1.1166 |
57
+ | No log | 0.1739 | 12 | 1.1872 | 0.1278 | 1.1872 | 1.0896 |
58
+ | No log | 0.2029 | 14 | 1.2824 | 0.0414 | 1.2824 | 1.1324 |
59
+ | No log | 0.2319 | 16 | 1.7128 | 0.0800 | 1.7128 | 1.3088 |
60
+ | No log | 0.2609 | 18 | 2.0344 | -0.0329 | 2.0344 | 1.4263 |
61
+ | No log | 0.2899 | 20 | 1.8209 | -0.0056 | 1.8209 | 1.3494 |
62
+ | No log | 0.3188 | 22 | 1.3645 | 0.1328 | 1.3645 | 1.1681 |
63
+ | No log | 0.3478 | 24 | 1.2135 | 0.0571 | 1.2135 | 1.1016 |
64
+ | No log | 0.3768 | 26 | 1.2184 | 0.0771 | 1.2184 | 1.1038 |
65
+ | No log | 0.4058 | 28 | 1.2310 | 0.0700 | 1.2310 | 1.1095 |
66
+ | No log | 0.4348 | 30 | 1.2650 | 0.1407 | 1.2650 | 1.1247 |
67
+ | No log | 0.4638 | 32 | 1.4134 | -0.0478 | 1.4134 | 1.1889 |
68
+ | No log | 0.4928 | 34 | 1.7308 | -0.0149 | 1.7308 | 1.3156 |
69
+ | No log | 0.5217 | 36 | 1.7938 | -0.0149 | 1.7938 | 1.3393 |
70
+ | No log | 0.5507 | 38 | 1.6445 | -0.0149 | 1.6445 | 1.2824 |
71
+ | No log | 0.5797 | 40 | 1.3834 | -0.0300 | 1.3834 | 1.1762 |
72
+ | No log | 0.6087 | 42 | 1.3220 | 0.0339 | 1.3220 | 1.1498 |
73
+ | No log | 0.6377 | 44 | 1.2841 | 0.1827 | 1.2841 | 1.1332 |
74
+ | No log | 0.6667 | 46 | 1.2250 | 0.0979 | 1.2250 | 1.1068 |
75
+ | No log | 0.6957 | 48 | 1.2127 | 0.1570 | 1.2127 | 1.1012 |
76
+ | No log | 0.7246 | 50 | 1.2186 | 0.1370 | 1.2186 | 1.1039 |
77
+ | No log | 0.7536 | 52 | 1.2021 | 0.1109 | 1.2021 | 1.0964 |
78
+ | No log | 0.7826 | 54 | 1.2031 | 0.1335 | 1.2031 | 1.0969 |
79
+ | No log | 0.8116 | 56 | 1.2084 | 0.2124 | 1.2084 | 1.0993 |
80
+ | No log | 0.8406 | 58 | 1.2694 | 0.1472 | 1.2694 | 1.1267 |
81
+ | No log | 0.8696 | 60 | 1.2556 | 0.1438 | 1.2556 | 1.1205 |
82
+ | No log | 0.8986 | 62 | 1.2124 | 0.2640 | 1.2124 | 1.1011 |
83
+ | No log | 0.9275 | 64 | 1.1949 | 0.3431 | 1.1949 | 1.0931 |
84
+ | No log | 0.9565 | 66 | 1.2473 | 0.1136 | 1.2473 | 1.1168 |
85
+ | No log | 0.9855 | 68 | 1.2373 | 0.1472 | 1.2373 | 1.1123 |
86
+ | No log | 1.0145 | 70 | 1.2641 | 0.1379 | 1.2641 | 1.1243 |
87
+ | No log | 1.0435 | 72 | 1.3004 | 0.1530 | 1.3004 | 1.1403 |
88
+ | No log | 1.0725 | 74 | 1.3691 | 0.0776 | 1.3691 | 1.1701 |
89
+ | No log | 1.1014 | 76 | 1.2826 | 0.1530 | 1.2826 | 1.1325 |
90
+ | No log | 1.1304 | 78 | 1.1783 | 0.1266 | 1.1783 | 1.0855 |
91
+ | No log | 1.1594 | 80 | 1.1526 | 0.1397 | 1.1526 | 1.0736 |
92
+ | No log | 1.1884 | 82 | 1.1191 | 0.2079 | 1.1191 | 1.0579 |
93
+ | No log | 1.2174 | 84 | 1.1289 | 0.2752 | 1.1289 | 1.0625 |
94
+ | No log | 1.2464 | 86 | 1.1001 | 0.2439 | 1.1001 | 1.0489 |
95
+ | No log | 1.2754 | 88 | 1.5160 | 0.0858 | 1.5160 | 1.2312 |
96
+ | No log | 1.3043 | 90 | 2.2418 | 0.1298 | 2.2418 | 1.4973 |
97
+ | No log | 1.3333 | 92 | 2.4552 | 0.1257 | 2.4552 | 1.5669 |
98
+ | No log | 1.3623 | 94 | 2.2870 | 0.1417 | 2.2870 | 1.5123 |
99
+ | No log | 1.3913 | 96 | 1.9482 | 0.0844 | 1.9482 | 1.3958 |
100
+ | No log | 1.4203 | 98 | 1.6126 | 0.1395 | 1.6126 | 1.2699 |
101
+ | No log | 1.4493 | 100 | 1.4523 | 0.1109 | 1.4523 | 1.2051 |
102
+ | No log | 1.4783 | 102 | 1.2206 | 0.1045 | 1.2206 | 1.1048 |
103
+ | No log | 1.5072 | 104 | 1.0651 | 0.3497 | 1.0651 | 1.0320 |
104
+ | No log | 1.5362 | 106 | 1.0518 | 0.2921 | 1.0518 | 1.0256 |
105
+ | No log | 1.5652 | 108 | 1.0573 | 0.3596 | 1.0573 | 1.0283 |
106
+ | No log | 1.5942 | 110 | 1.0892 | 0.2605 | 1.0892 | 1.0436 |
107
+ | No log | 1.6232 | 112 | 1.0880 | 0.2605 | 1.0880 | 1.0431 |
108
+ | No log | 1.6522 | 114 | 1.0441 | 0.3015 | 1.0441 | 1.0218 |
109
+ | No log | 1.6812 | 116 | 1.0387 | 0.2973 | 1.0387 | 1.0192 |
110
+ | No log | 1.7101 | 118 | 1.0727 | 0.3488 | 1.0727 | 1.0357 |
111
+ | No log | 1.7391 | 120 | 1.0565 | 0.3394 | 1.0565 | 1.0278 |
112
+ | No log | 1.7681 | 122 | 1.0438 | 0.3186 | 1.0438 | 1.0217 |
113
+ | No log | 1.7971 | 124 | 1.1187 | 0.2826 | 1.1187 | 1.0577 |
114
+ | No log | 1.8261 | 126 | 1.0742 | 0.3857 | 1.0742 | 1.0364 |
115
+ | No log | 1.8551 | 128 | 1.0530 | 0.3405 | 1.0530 | 1.0262 |
116
+ | No log | 1.8841 | 130 | 1.0615 | 0.2522 | 1.0615 | 1.0303 |
117
+ | No log | 1.9130 | 132 | 1.0671 | 0.1793 | 1.0671 | 1.0330 |
118
+ | No log | 1.9420 | 134 | 1.0981 | 0.2323 | 1.0981 | 1.0479 |
119
+ | No log | 1.9710 | 136 | 1.0870 | 0.1495 | 1.0870 | 1.0426 |
120
+ | No log | 2.0 | 138 | 1.0625 | 0.2486 | 1.0625 | 1.0308 |
121
+ | No log | 2.0290 | 140 | 1.1616 | 0.2953 | 1.1616 | 1.0778 |
122
+ | No log | 2.0580 | 142 | 1.2757 | 0.2837 | 1.2757 | 1.1295 |
123
+ | No log | 2.0870 | 144 | 1.2220 | 0.2570 | 1.2220 | 1.1054 |
124
+ | No log | 2.1159 | 146 | 1.1424 | 0.2448 | 1.1424 | 1.0688 |
125
+ | No log | 2.1449 | 148 | 1.1899 | 0.1579 | 1.1899 | 1.0908 |
126
+ | No log | 2.1739 | 150 | 1.2449 | 0.1761 | 1.2449 | 1.1157 |
127
+ | No log | 2.2029 | 152 | 1.1871 | 0.2199 | 1.1871 | 1.0895 |
128
+ | No log | 2.2319 | 154 | 1.2411 | 0.2273 | 1.2411 | 1.1140 |
129
+ | No log | 2.2609 | 156 | 1.1858 | 0.2001 | 1.1858 | 1.0889 |
130
+ | No log | 2.2899 | 158 | 1.1664 | 0.2061 | 1.1664 | 1.0800 |
131
+ | No log | 2.3188 | 160 | 1.2772 | 0.2743 | 1.2772 | 1.1301 |
132
+ | No log | 2.3478 | 162 | 1.2680 | 0.2154 | 1.2680 | 1.1261 |
133
+ | No log | 2.3768 | 164 | 1.3124 | 0.0324 | 1.3124 | 1.1456 |
134
+ | No log | 2.4058 | 166 | 1.2881 | 0.1706 | 1.2881 | 1.1349 |
135
+ | No log | 2.4348 | 168 | 1.3298 | 0.1316 | 1.3298 | 1.1532 |
136
+ | No log | 2.4638 | 170 | 1.3042 | 0.1637 | 1.3042 | 1.1420 |
137
+ | No log | 2.4928 | 172 | 1.1637 | 0.1249 | 1.1637 | 1.0788 |
138
+ | No log | 2.5217 | 174 | 1.1146 | 0.1685 | 1.1146 | 1.0558 |
139
+ | No log | 2.5507 | 176 | 1.0708 | 0.2117 | 1.0708 | 1.0348 |
140
+ | No log | 2.5797 | 178 | 1.0520 | 0.2917 | 1.0520 | 1.0257 |
141
+ | No log | 2.6087 | 180 | 1.0194 | 0.3478 | 1.0194 | 1.0096 |
142
+ | No log | 2.6377 | 182 | 1.0313 | 0.2965 | 1.0313 | 1.0155 |
143
+ | No log | 2.6667 | 184 | 1.1415 | 0.3152 | 1.1415 | 1.0684 |
144
+ | No log | 2.6957 | 186 | 1.1166 | 0.2372 | 1.1166 | 1.0567 |
145
+ | No log | 2.7246 | 188 | 1.0718 | 0.2893 | 1.0718 | 1.0353 |
146
+ | No log | 2.7536 | 190 | 1.2480 | 0.2046 | 1.2480 | 1.1172 |
147
+ | No log | 2.7826 | 192 | 1.5400 | 0.2521 | 1.5400 | 1.2410 |
148
+ | No log | 2.8116 | 194 | 1.4287 | 0.2947 | 1.4287 | 1.1953 |
149
+ | No log | 2.8406 | 196 | 1.1192 | 0.2623 | 1.1192 | 1.0579 |
150
+ | No log | 2.8696 | 198 | 1.0862 | 0.2476 | 1.0862 | 1.0422 |
151
+ | No log | 2.8986 | 200 | 1.1361 | 0.2380 | 1.1361 | 1.0659 |
152
+ | No log | 2.9275 | 202 | 1.0357 | 0.3179 | 1.0357 | 1.0177 |
153
+ | No log | 2.9565 | 204 | 1.0499 | 0.4519 | 1.0499 | 1.0247 |
154
+ | No log | 2.9855 | 206 | 1.1459 | 0.4048 | 1.1459 | 1.0705 |
155
+ | No log | 3.0145 | 208 | 1.0606 | 0.4924 | 1.0606 | 1.0299 |
156
+ | No log | 3.0435 | 210 | 1.0682 | 0.4986 | 1.0682 | 1.0335 |
157
+ | No log | 3.0725 | 212 | 1.0640 | 0.4986 | 1.0640 | 1.0315 |
158
+ | No log | 3.1014 | 214 | 1.0180 | 0.4826 | 1.0180 | 1.0090 |
159
+ | No log | 3.1304 | 216 | 0.9791 | 0.4398 | 0.9791 | 0.9895 |
160
+ | No log | 3.1594 | 218 | 0.9636 | 0.3418 | 0.9636 | 0.9816 |
161
+ | No log | 3.1884 | 220 | 0.9579 | 0.3854 | 0.9579 | 0.9787 |
162
+ | No log | 3.2174 | 222 | 0.9729 | 0.3720 | 0.9729 | 0.9864 |
163
+ | No log | 3.2464 | 224 | 1.0259 | 0.3897 | 1.0259 | 1.0129 |
164
+ | No log | 3.2754 | 226 | 1.0143 | 0.4028 | 1.0143 | 1.0071 |
165
+ | No log | 3.3043 | 228 | 0.9307 | 0.3854 | 0.9307 | 0.9647 |
166
+ | No log | 3.3333 | 230 | 0.9870 | 0.3110 | 0.9870 | 0.9935 |
167
+ | No log | 3.3623 | 232 | 1.0668 | 0.3056 | 1.0668 | 1.0328 |
168
+ | No log | 3.3913 | 234 | 0.9838 | 0.3602 | 0.9838 | 0.9918 |
169
+ | No log | 3.4203 | 236 | 0.9037 | 0.3896 | 0.9037 | 0.9506 |
170
+ | No log | 3.4493 | 238 | 0.9677 | 0.4568 | 0.9677 | 0.9837 |
171
+ | No log | 3.4783 | 240 | 0.9574 | 0.4476 | 0.9574 | 0.9785 |
172
+ | No log | 3.5072 | 242 | 0.9393 | 0.3641 | 0.9393 | 0.9692 |
173
+ | No log | 3.5362 | 244 | 0.9574 | 0.2864 | 0.9574 | 0.9784 |
174
+ | No log | 3.5652 | 246 | 0.9483 | 0.3629 | 0.9483 | 0.9738 |
175
+ | No log | 3.5942 | 248 | 0.9728 | 0.4059 | 0.9728 | 0.9863 |
176
+ | No log | 3.6232 | 250 | 0.9850 | 0.3278 | 0.9850 | 0.9925 |
177
+ | No log | 3.6522 | 252 | 0.9950 | 0.3383 | 0.9950 | 0.9975 |
178
+ | No log | 3.6812 | 254 | 1.0111 | 0.2812 | 1.0111 | 1.0055 |
179
+ | No log | 3.7101 | 256 | 1.0400 | 0.3202 | 1.0400 | 1.0198 |
180
+ | No log | 3.7391 | 258 | 1.0701 | 0.2998 | 1.0701 | 1.0345 |
181
+ | No log | 3.7681 | 260 | 1.0727 | 0.3263 | 1.0727 | 1.0357 |
182
+ | No log | 3.7971 | 262 | 1.1209 | 0.3647 | 1.1209 | 1.0587 |
183
+ | No log | 3.8261 | 264 | 1.1999 | 0.4186 | 1.1999 | 1.0954 |
184
+ | No log | 3.8551 | 266 | 1.3750 | 0.3449 | 1.3750 | 1.1726 |
185
+ | No log | 3.8841 | 268 | 1.4418 | 0.3541 | 1.4418 | 1.2007 |
186
+ | No log | 3.9130 | 270 | 1.3385 | 0.4010 | 1.3385 | 1.1569 |
187
+ | No log | 3.9420 | 272 | 1.1344 | 0.4186 | 1.1344 | 1.0651 |
188
+ | No log | 3.9710 | 274 | 1.0099 | 0.3866 | 1.0099 | 1.0049 |
189
+ | No log | 4.0 | 276 | 1.0131 | 0.3318 | 1.0131 | 1.0065 |
190
+ | No log | 4.0290 | 278 | 1.0656 | 0.3540 | 1.0656 | 1.0323 |
191
+ | No log | 4.0580 | 280 | 1.0861 | 0.3540 | 1.0861 | 1.0422 |
192
+ | No log | 4.0870 | 282 | 1.1390 | 0.4186 | 1.1390 | 1.0673 |
193
+ | No log | 4.1159 | 284 | 1.1262 | 0.4186 | 1.1262 | 1.0612 |
194
+ | No log | 4.1449 | 286 | 1.0343 | 0.3518 | 1.0343 | 1.0170 |
195
+ | No log | 4.1739 | 288 | 0.9972 | 0.3643 | 0.9972 | 0.9986 |
196
+ | No log | 4.2029 | 290 | 1.0081 | 0.3729 | 1.0081 | 1.0040 |
197
+ | No log | 4.2319 | 292 | 1.0896 | 0.3657 | 1.0896 | 1.0438 |
198
+ | No log | 4.2609 | 294 | 1.0946 | 0.4096 | 1.0946 | 1.0462 |
199
+ | No log | 4.2899 | 296 | 0.9811 | 0.3771 | 0.9811 | 0.9905 |
200
+ | No log | 4.3188 | 298 | 0.9845 | 0.2941 | 0.9845 | 0.9922 |
201
+ | No log | 4.3478 | 300 | 0.9867 | 0.2941 | 0.9867 | 0.9933 |
202
+ | No log | 4.3768 | 302 | 0.9870 | 0.2364 | 0.9870 | 0.9935 |
203
+ | No log | 4.4058 | 304 | 0.9751 | 0.3762 | 0.9751 | 0.9875 |
204
+ | No log | 4.4348 | 306 | 1.0293 | 0.4065 | 1.0293 | 1.0145 |
205
+ | No log | 4.4638 | 308 | 1.0085 | 0.4062 | 1.0085 | 1.0042 |
206
+ | No log | 4.4928 | 310 | 1.0061 | 0.4062 | 1.0061 | 1.0030 |
207
+ | No log | 4.5217 | 312 | 1.0253 | 0.3777 | 1.0253 | 1.0126 |
208
+ | No log | 4.5507 | 314 | 1.0420 | 0.3590 | 1.0420 | 1.0208 |
209
+ | No log | 4.5797 | 316 | 1.0758 | 0.3196 | 1.0758 | 1.0372 |
210
+ | No log | 4.6087 | 318 | 1.1391 | 0.3474 | 1.1391 | 1.0673 |
211
+ | No log | 4.6377 | 320 | 1.1945 | 0.3528 | 1.1945 | 1.0929 |
212
+ | No log | 4.6667 | 322 | 1.2194 | 0.3148 | 1.2194 | 1.1043 |
213
+ | No log | 4.6957 | 324 | 1.1883 | 0.3540 | 1.1883 | 1.0901 |
214
+ | No log | 4.7246 | 326 | 1.0794 | 0.4354 | 1.0794 | 1.0390 |
215
+ | No log | 4.7536 | 328 | 1.0791 | 0.4129 | 1.0791 | 1.0388 |
216
+ | No log | 4.7826 | 330 | 1.1650 | 0.3755 | 1.1650 | 1.0794 |
217
+ | No log | 4.8116 | 332 | 1.2404 | 0.3863 | 1.2404 | 1.1137 |
218
+ | No log | 4.8406 | 334 | 1.1511 | 0.3958 | 1.1511 | 1.0729 |
219
+ | No log | 4.8696 | 336 | 1.0460 | 0.3073 | 1.0460 | 1.0227 |
220
+ | No log | 4.8986 | 338 | 1.0631 | 0.2894 | 1.0631 | 1.0311 |
221
+ | No log | 4.9275 | 340 | 1.0357 | 0.3202 | 1.0357 | 1.0177 |
222
+ | No log | 4.9565 | 342 | 1.0054 | 0.2658 | 1.0054 | 1.0027 |
223
+ | No log | 4.9855 | 344 | 0.9858 | 0.2658 | 0.9858 | 0.9929 |
224
+ | No log | 5.0145 | 346 | 0.9589 | 0.3223 | 0.9589 | 0.9792 |
225
+ | No log | 5.0435 | 348 | 0.9356 | 0.3119 | 0.9356 | 0.9672 |
226
+ | No log | 5.0725 | 350 | 0.9251 | 0.3119 | 0.9251 | 0.9618 |
227
+ | No log | 5.1014 | 352 | 0.9167 | 0.3119 | 0.9167 | 0.9574 |
228
+ | No log | 5.1304 | 354 | 0.9110 | 0.3421 | 0.9110 | 0.9545 |
229
+ | No log | 5.1594 | 356 | 0.8973 | 0.3421 | 0.8973 | 0.9472 |
230
+ | No log | 5.1884 | 358 | 0.8751 | 0.3119 | 0.8751 | 0.9355 |
231
+ | No log | 5.2174 | 360 | 0.8777 | 0.3017 | 0.8777 | 0.9368 |
232
+ | No log | 5.2464 | 362 | 0.8761 | 0.3804 | 0.8761 | 0.9360 |
233
+ | No log | 5.2754 | 364 | 0.9242 | 0.4429 | 0.9242 | 0.9613 |
234
+ | No log | 5.3043 | 366 | 0.9219 | 0.4105 | 0.9219 | 0.9602 |
235
+ | No log | 5.3333 | 368 | 0.9103 | 0.3861 | 0.9103 | 0.9541 |
236
+ | No log | 5.3623 | 370 | 0.9512 | 0.3970 | 0.9512 | 0.9753 |
237
+ | No log | 5.3913 | 372 | 0.9702 | 0.4297 | 0.9702 | 0.9850 |
238
+ | No log | 5.4203 | 374 | 1.0207 | 0.4591 | 1.0207 | 1.0103 |
239
+ | No log | 5.4493 | 376 | 0.9832 | 0.4295 | 0.9832 | 0.9916 |
240
+ | No log | 5.4783 | 378 | 0.9356 | 0.3522 | 0.9356 | 0.9673 |
241
+ | No log | 5.5072 | 380 | 0.9386 | 0.3424 | 0.9386 | 0.9688 |
242
+ | No log | 5.5362 | 382 | 0.9778 | 0.3970 | 0.9778 | 0.9889 |
243
+ | No log | 5.5652 | 384 | 1.1905 | 0.4390 | 1.1905 | 1.0911 |
244
+ | No log | 5.5942 | 386 | 1.3485 | 0.3765 | 1.3485 | 1.1613 |
245
+ | No log | 5.6232 | 388 | 1.3217 | 0.3621 | 1.3217 | 1.1497 |
246
+ | No log | 5.6522 | 390 | 1.1887 | 0.2826 | 1.1887 | 1.0903 |
247
+ | No log | 5.6812 | 392 | 1.1260 | 0.3657 | 1.1260 | 1.0611 |
248
+ | No log | 5.7101 | 394 | 1.0679 | 0.4257 | 1.0679 | 1.0334 |
249
+ | No log | 5.7391 | 396 | 1.0633 | 0.4468 | 1.0633 | 1.0312 |
250
+ | No log | 5.7681 | 398 | 1.0476 | 0.5190 | 1.0476 | 1.0235 |
251
+ | No log | 5.7971 | 400 | 0.9732 | 0.4382 | 0.9732 | 0.9865 |
252
+ | No log | 5.8261 | 402 | 0.9216 | 0.4429 | 0.9216 | 0.9600 |
253
+ | No log | 5.8551 | 404 | 0.9368 | 0.4622 | 0.9368 | 0.9679 |
254
+ | No log | 5.8841 | 406 | 1.0060 | 0.4257 | 1.0060 | 1.0030 |
255
+ | No log | 5.9130 | 408 | 1.0549 | 0.4130 | 1.0549 | 1.0271 |
256
+ | No log | 5.9420 | 410 | 1.0562 | 0.4130 | 1.0562 | 1.0277 |
257
+ | No log | 5.9710 | 412 | 1.0207 | 0.4484 | 1.0207 | 1.0103 |
258
+ | No log | 6.0 | 414 | 0.9874 | 0.4261 | 0.9874 | 0.9937 |
259
+ | No log | 6.0290 | 416 | 1.0001 | 0.4261 | 1.0001 | 1.0000 |
260
+ | No log | 6.0580 | 418 | 1.1090 | 0.4430 | 1.1090 | 1.0531 |
261
+ | No log | 6.0870 | 420 | 1.1470 | 0.4633 | 1.1470 | 1.0710 |
262
+ | No log | 6.1159 | 422 | 1.0881 | 0.4468 | 1.0881 | 1.0431 |
263
+ | No log | 6.1449 | 424 | 1.0284 | 0.4261 | 1.0284 | 1.0141 |
264
+ | No log | 6.1739 | 426 | 1.0208 | 0.3687 | 1.0208 | 1.0103 |
265
+ | No log | 6.2029 | 428 | 1.0655 | 0.4262 | 1.0655 | 1.0322 |
266
+ | No log | 6.2319 | 430 | 1.1834 | 0.4007 | 1.1834 | 1.0879 |
267
+ | No log | 6.2609 | 432 | 1.2332 | 0.3676 | 1.2332 | 1.1105 |
268
+ | No log | 6.2899 | 434 | 1.2002 | 0.3438 | 1.2002 | 1.0955 |
269
+ | No log | 6.3188 | 436 | 1.0745 | 0.3645 | 1.0745 | 1.0366 |
270
+ | No log | 6.3478 | 438 | 0.9878 | 0.2944 | 0.9878 | 0.9939 |
271
+ | No log | 6.3768 | 440 | 1.0073 | 0.2965 | 1.0073 | 1.0036 |
272
+ | No log | 6.4058 | 442 | 1.0036 | 0.2562 | 1.0036 | 1.0018 |
273
+ | No log | 6.4348 | 444 | 1.0010 | 0.3418 | 1.0010 | 1.0005 |
274
+ | No log | 6.4638 | 446 | 1.1105 | 0.3785 | 1.1105 | 1.0538 |
275
+ | No log | 6.4928 | 448 | 1.2206 | 0.3440 | 1.2206 | 1.1048 |
276
+ | No log | 6.5217 | 450 | 1.3041 | 0.4457 | 1.3041 | 1.1420 |
277
+ | No log | 6.5507 | 452 | 1.2407 | 0.4069 | 1.2407 | 1.1139 |
278
+ | No log | 6.5797 | 454 | 1.0604 | 0.3996 | 1.0604 | 1.0298 |
279
+ | No log | 6.6087 | 456 | 0.9901 | 0.4021 | 0.9901 | 0.9950 |
280
+ | No log | 6.6377 | 458 | 0.9837 | 0.3250 | 0.9837 | 0.9918 |
281
+ | No log | 6.6667 | 460 | 0.9689 | 0.3250 | 0.9689 | 0.9843 |
282
+ | No log | 6.6957 | 462 | 0.9731 | 0.4021 | 0.9731 | 0.9864 |
283
+ | No log | 6.7246 | 464 | 0.9616 | 0.3666 | 0.9616 | 0.9806 |
284
+ | No log | 6.7536 | 466 | 0.9392 | 0.3666 | 0.9392 | 0.9691 |
285
+ | No log | 6.7826 | 468 | 0.9212 | 0.2743 | 0.9212 | 0.9598 |
286
+ | No log | 6.8116 | 470 | 0.9212 | 0.2515 | 0.9212 | 0.9598 |
287
+ | No log | 6.8406 | 472 | 0.9239 | 0.3039 | 0.9239 | 0.9612 |
288
+ | No log | 6.8696 | 474 | 0.9444 | 0.2843 | 0.9444 | 0.9718 |
289
+ | No log | 6.8986 | 476 | 0.9248 | 0.2991 | 0.9248 | 0.9617 |
290
+ | No log | 6.9275 | 478 | 0.9312 | 0.3753 | 0.9312 | 0.9650 |
291
+ | No log | 6.9565 | 480 | 0.9394 | 0.3744 | 0.9394 | 0.9692 |
292
+ | No log | 6.9855 | 482 | 0.9398 | 0.3223 | 0.9398 | 0.9694 |
293
+ | No log | 7.0145 | 484 | 0.9602 | 0.3326 | 0.9602 | 0.9799 |
294
+ | No log | 7.0435 | 486 | 0.9929 | 0.3298 | 0.9929 | 0.9964 |
295
+ | No log | 7.0725 | 488 | 1.0202 | 0.3250 | 1.0202 | 1.0100 |
296
+ | No log | 7.1014 | 490 | 1.0475 | 0.2843 | 1.0475 | 1.0235 |
297
+ | No log | 7.1304 | 492 | 1.0601 | 0.3885 | 1.0601 | 1.0296 |
298
+ | No log | 7.1594 | 494 | 1.0520 | 0.4264 | 1.0520 | 1.0257 |
299
+ | No log | 7.1884 | 496 | 1.0224 | 0.4402 | 1.0224 | 1.0111 |
300
+ | No log | 7.2174 | 498 | 1.0075 | 0.4302 | 1.0075 | 1.0037 |
301
+ | 0.4282 | 7.2464 | 500 | 1.0417 | 0.4402 | 1.0417 | 1.0206 |
302
+ | 0.4282 | 7.2754 | 502 | 1.0546 | 0.4165 | 1.0546 | 1.0270 |
303
+ | 0.4282 | 7.3043 | 504 | 0.9900 | 0.4676 | 0.9900 | 0.9950 |
304
+ | 0.4282 | 7.3333 | 506 | 0.9462 | 0.4343 | 0.9462 | 0.9727 |
305
+ | 0.4282 | 7.3623 | 508 | 0.9407 | 0.4343 | 0.9407 | 0.9699 |
306
+ | 0.4282 | 7.3913 | 510 | 0.9688 | 0.4676 | 0.9688 | 0.9843 |
307
+ | 0.4282 | 7.4203 | 512 | 1.0183 | 0.4814 | 1.0183 | 1.0091 |
308
+ | 0.4282 | 7.4493 | 514 | 1.0876 | 0.4222 | 1.0876 | 1.0429 |
309
+ | 0.4282 | 7.4783 | 516 | 1.0669 | 0.3870 | 1.0669 | 1.0329 |
310
+ | 0.4282 | 7.5072 | 518 | 0.9761 | 0.4777 | 0.9761 | 0.9880 |
311
+ | 0.4282 | 7.5362 | 520 | 0.9401 | 0.4340 | 0.9401 | 0.9696 |
312
+ | 0.4282 | 7.5652 | 522 | 0.9614 | 0.4331 | 0.9614 | 0.9805 |
313
+ | 0.4282 | 7.5942 | 524 | 1.0239 | 0.4803 | 1.0239 | 1.0119 |
314
+ | 0.4282 | 7.6232 | 526 | 0.9753 | 0.4546 | 0.9753 | 0.9876 |
315
+ | 0.4282 | 7.6522 | 528 | 0.9234 | 0.4002 | 0.9234 | 0.9610 |
316
+ | 0.4282 | 7.6812 | 530 | 0.9071 | 0.3243 | 0.9071 | 0.9524 |
317
+ | 0.4282 | 7.7101 | 532 | 0.9121 | 0.3508 | 0.9121 | 0.9550 |
318
+ | 0.4282 | 7.7391 | 534 | 0.9111 | 0.4002 | 0.9111 | 0.9545 |
319
+ | 0.4282 | 7.7681 | 536 | 0.8956 | 0.3243 | 0.8956 | 0.9464 |
320
+
321
+
322
+ ### Framework versions
323
+
324
+ - Transformers 4.44.2
325
+ - Pytorch 2.4.0+cu118
326
+ - Datasets 2.21.0
327
+ - 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 sha256:028de4c0f1ff428c1be4ae48627dfc2c1027bd26fbc9521a452e0e0b75caf580
3
+ size 540799996
training_args.bin ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:e1b7804f41c496bbacfded40d3600d12a2e70944169f70095f4c18eb2c716ac0
3
+ size 5368