Hugging Face's logo

MayBashendy
/
ArabicNewSplits7_usingWellWrittenEssays_FineTuningAraBERT_run3_AugV5_k20_task7_organization

Text Classification
Transformers
Safetensors
bert
Generated from Trainer
Model card Files
xet
 Community
MayBashendy commited on
Commit
6266db2
·
verified ·
1 Parent(s): 65be72e

Training in progress, step 500

Browse files
Files changed (4) hide show
  1. README.md +322 -0
  2. config.json +32 -0
  3. model.safetensors +3 -0
  4. training_args.bin +3 -0
README.md ADDED
@@ -0,0 +1,322 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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_run3_AugV5_k19_task7_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_run3_AugV5_k19_task7_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: 0.7500
19
+ - Qwk: 0.2685
20
+ - Mse: 0.7500
21
+ - Rmse: 0.8660
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 | 0.0444 | 2 | 2.6359 | -0.0262 | 2.6359 | 1.6235 |
53
+ | No log | 0.0889 | 4 | 1.3851 | 0.0750 | 1.3851 | 1.1769 |
54
+ | No log | 0.1333 | 6 | 1.2984 | -0.1983 | 1.2984 | 1.1395 |
55
+ | No log | 0.1778 | 8 | 1.2589 | -0.2787 | 1.2589 | 1.1220 |
56
+ | No log | 0.2222 | 10 | 1.1997 | -0.1356 | 1.1997 | 1.0953 |
57
+ | No log | 0.2667 | 12 | 1.2070 | -0.1705 | 1.2070 | 1.0986 |
58
+ | No log | 0.3111 | 14 | 1.3576 | -0.1384 | 1.3576 | 1.1652 |
59
+ | No log | 0.3556 | 16 | 1.6718 | 0.0289 | 1.6718 | 1.2930 |
60
+ | No log | 0.4 | 18 | 1.5585 | 0.0278 | 1.5585 | 1.2484 |
61
+ | No log | 0.4444 | 20 | 1.1516 | -0.0961 | 1.1516 | 1.0731 |
62
+ | No log | 0.4889 | 22 | 0.9965 | -0.0288 | 0.9965 | 0.9982 |
63
+ | No log | 0.5333 | 24 | 0.8746 | 0.0725 | 0.8746 | 0.9352 |
64
+ | No log | 0.5778 | 26 | 0.8535 | 0.0410 | 0.8535 | 0.9238 |
65
+ | No log | 0.6222 | 28 | 0.8574 | 0.0937 | 0.8574 | 0.9260 |
66
+ | No log | 0.6667 | 30 | 0.8894 | 0.0509 | 0.8894 | 0.9431 |
67
+ | No log | 0.7111 | 32 | 0.8933 | 0.0947 | 0.8933 | 0.9452 |
68
+ | No log | 0.7556 | 34 | 0.9631 | 0.0609 | 0.9631 | 0.9814 |
69
+ | No log | 0.8 | 36 | 1.0418 | 0.0329 | 1.0418 | 1.0207 |
70
+ | No log | 0.8444 | 38 | 1.1758 | 0.0095 | 1.1758 | 1.0843 |
71
+ | No log | 0.8889 | 40 | 1.1874 | 0.0126 | 1.1874 | 1.0897 |
72
+ | No log | 0.9333 | 42 | 0.9553 | -0.0484 | 0.9553 | 0.9774 |
73
+ | No log | 0.9778 | 44 | 0.8113 | 0.1737 | 0.8113 | 0.9007 |
74
+ | No log | 1.0222 | 46 | 0.9473 | 0.2651 | 0.9473 | 0.9733 |
75
+ | No log | 1.0667 | 48 | 1.0228 | 0.2757 | 1.0228 | 1.0113 |
76
+ | No log | 1.1111 | 50 | 1.0274 | 0.2543 | 1.0274 | 1.0136 |
77
+ | No log | 1.1556 | 52 | 0.8946 | 0.2063 | 0.8946 | 0.9458 |
78
+ | No log | 1.2 | 54 | 0.7827 | 0.0757 | 0.7827 | 0.8847 |
79
+ | No log | 1.2444 | 56 | 0.8118 | 0.0804 | 0.8118 | 0.9010 |
80
+ | No log | 1.2889 | 58 | 0.9450 | 0.0506 | 0.9450 | 0.9721 |
81
+ | No log | 1.3333 | 60 | 1.1381 | 0.0661 | 1.1381 | 1.0668 |
82
+ | No log | 1.3778 | 62 | 1.1565 | 0.0643 | 1.1565 | 1.0754 |
83
+ | No log | 1.4222 | 64 | 1.0107 | 0.2092 | 1.0107 | 1.0053 |
84
+ | No log | 1.4667 | 66 | 0.9388 | 0.2034 | 0.9388 | 0.9689 |
85
+ | No log | 1.5111 | 68 | 0.9827 | 0.2118 | 0.9827 | 0.9913 |
86
+ | No log | 1.5556 | 70 | 1.0083 | 0.1460 | 1.0083 | 1.0041 |
87
+ | No log | 1.6 | 72 | 0.9885 | 0.0823 | 0.9885 | 0.9942 |
88
+ | No log | 1.6444 | 74 | 1.0196 | 0.1153 | 1.0196 | 1.0098 |
89
+ | No log | 1.6889 | 76 | 0.9374 | 0.0813 | 0.9374 | 0.9682 |
90
+ | No log | 1.7333 | 78 | 0.8498 | 0.0 | 0.8498 | 0.9218 |
91
+ | No log | 1.7778 | 80 | 0.8160 | 0.1440 | 0.8160 | 0.9033 |
92
+ | No log | 1.8222 | 82 | 0.8221 | 0.1440 | 0.8221 | 0.9067 |
93
+ | No log | 1.8667 | 84 | 0.8814 | 0.0727 | 0.8814 | 0.9388 |
94
+ | No log | 1.9111 | 86 | 1.0439 | 0.1427 | 1.0439 | 1.0217 |
95
+ | No log | 1.9556 | 88 | 1.0434 | 0.1122 | 1.0434 | 1.0214 |
96
+ | No log | 2.0 | 90 | 1.0136 | 0.0722 | 1.0136 | 1.0068 |
97
+ | No log | 2.0444 | 92 | 0.9971 | 0.1311 | 0.9971 | 0.9986 |
98
+ | No log | 2.0889 | 94 | 0.9859 | 0.1627 | 0.9859 | 0.9929 |
99
+ | No log | 2.1333 | 96 | 0.9564 | 0.1627 | 0.9564 | 0.9779 |
100
+ | No log | 2.1778 | 98 | 0.9328 | 0.1289 | 0.9328 | 0.9658 |
101
+ | No log | 2.2222 | 100 | 0.9468 | 0.1661 | 0.9468 | 0.9730 |
102
+ | No log | 2.2667 | 102 | 0.9298 | 0.1289 | 0.9298 | 0.9643 |
103
+ | No log | 2.3111 | 104 | 1.0249 | 0.1121 | 1.0249 | 1.0124 |
104
+ | No log | 2.3556 | 106 | 0.9742 | 0.1419 | 0.9742 | 0.9870 |
105
+ | No log | 2.4 | 108 | 0.8918 | 0.1410 | 0.8918 | 0.9443 |
106
+ | No log | 2.4444 | 110 | 0.8916 | 0.1455 | 0.8916 | 0.9443 |
107
+ | No log | 2.4889 | 112 | 0.8683 | 0.1684 | 0.8683 | 0.9318 |
108
+ | No log | 2.5333 | 114 | 0.8725 | 0.1986 | 0.8725 | 0.9341 |
109
+ | No log | 2.5778 | 116 | 0.8877 | 0.2279 | 0.8877 | 0.9422 |
110
+ | No log | 2.6222 | 118 | 0.9302 | 0.2192 | 0.9302 | 0.9645 |
111
+ | No log | 2.6667 | 120 | 0.9946 | 0.1801 | 0.9946 | 0.9973 |
112
+ | No log | 2.7111 | 122 | 0.9408 | 0.2053 | 0.9408 | 0.9699 |
113
+ | No log | 2.7556 | 124 | 0.9338 | 0.2256 | 0.9338 | 0.9663 |
114
+ | No log | 2.8 | 126 | 0.9154 | 0.2172 | 0.9154 | 0.9568 |
115
+ | No log | 2.8444 | 128 | 0.9245 | 0.1901 | 0.9245 | 0.9615 |
116
+ | No log | 2.8889 | 130 | 0.8507 | 0.2099 | 0.8507 | 0.9224 |
117
+ | No log | 2.9333 | 132 | 0.8177 | 0.2099 | 0.8177 | 0.9043 |
118
+ | No log | 2.9778 | 134 | 0.8226 | 0.1373 | 0.8226 | 0.9070 |
119
+ | No log | 3.0222 | 136 | 0.7946 | 0.2748 | 0.7946 | 0.8914 |
120
+ | No log | 3.0667 | 138 | 0.7981 | 0.2413 | 0.7981 | 0.8933 |
121
+ | No log | 3.1111 | 140 | 0.8029 | 0.2413 | 0.8029 | 0.8961 |
122
+ | No log | 3.1556 | 142 | 0.8052 | 0.2224 | 0.8052 | 0.8973 |
123
+ | No log | 3.2 | 144 | 0.8031 | 0.2193 | 0.8031 | 0.8962 |
124
+ | No log | 3.2444 | 146 | 0.7992 | 0.2224 | 0.7992 | 0.8940 |
125
+ | No log | 3.2889 | 148 | 0.7866 | 0.2224 | 0.7866 | 0.8869 |
126
+ | No log | 3.3333 | 150 | 0.7898 | 0.2398 | 0.7898 | 0.8887 |
127
+ | No log | 3.3778 | 152 | 0.7803 | 0.1733 | 0.7803 | 0.8833 |
128
+ | No log | 3.4222 | 154 | 0.8808 | 0.3942 | 0.8808 | 0.9385 |
129
+ | No log | 3.4667 | 156 | 1.0198 | 0.2702 | 1.0198 | 1.0099 |
130
+ | No log | 3.5111 | 158 | 1.0107 | 0.3068 | 1.0107 | 1.0053 |
131
+ | No log | 3.5556 | 160 | 0.8835 | 0.3007 | 0.8835 | 0.9400 |
132
+ | No log | 3.6 | 162 | 0.9044 | 0.2287 | 0.9044 | 0.9510 |
133
+ | No log | 3.6444 | 164 | 0.9069 | 0.2929 | 0.9069 | 0.9523 |
134
+ | No log | 3.6889 | 166 | 1.0188 | 0.3115 | 1.0188 | 1.0094 |
135
+ | No log | 3.7333 | 168 | 1.3046 | 0.0996 | 1.3046 | 1.1422 |
136
+ | No log | 3.7778 | 170 | 1.2620 | 0.1270 | 1.2620 | 1.1234 |
137
+ | No log | 3.8222 | 172 | 1.0842 | 0.2066 | 1.0842 | 1.0413 |
138
+ | No log | 3.8667 | 174 | 0.9470 | 0.1627 | 0.9470 | 0.9732 |
139
+ | No log | 3.9111 | 176 | 0.9380 | 0.1361 | 0.9380 | 0.9685 |
140
+ | No log | 3.9556 | 178 | 0.9032 | 0.1935 | 0.9032 | 0.9504 |
141
+ | No log | 4.0 | 180 | 0.9452 | 0.3023 | 0.9452 | 0.9722 |
142
+ | No log | 4.0444 | 182 | 1.0394 | 0.2437 | 1.0394 | 1.0195 |
143
+ | No log | 4.0889 | 184 | 1.0009 | 0.2467 | 1.0009 | 1.0005 |
144
+ | No log | 4.1333 | 186 | 0.9162 | 0.3015 | 0.9162 | 0.9572 |
145
+ | No log | 4.1778 | 188 | 0.9069 | 0.3015 | 0.9069 | 0.9523 |
146
+ | No log | 4.2222 | 190 | 0.9778 | 0.3195 | 0.9778 | 0.9888 |
147
+ | No log | 4.2667 | 192 | 0.9919 | 0.3675 | 0.9919 | 0.9960 |
148
+ | No log | 4.3111 | 194 | 0.8840 | 0.2359 | 0.8840 | 0.9402 |
149
+ | No log | 4.3556 | 196 | 0.8214 | 0.2279 | 0.8214 | 0.9063 |
150
+ | No log | 4.4 | 198 | 0.8172 | 0.1970 | 0.8172 | 0.9040 |
151
+ | No log | 4.4444 | 200 | 0.9355 | 0.2294 | 0.9355 | 0.9672 |
152
+ | No log | 4.4889 | 202 | 1.2532 | 0.2062 | 1.2532 | 1.1195 |
153
+ | No log | 4.5333 | 204 | 1.2852 | 0.1814 | 1.2852 | 1.1337 |
154
+ | No log | 4.5778 | 206 | 1.0131 | 0.2728 | 1.0131 | 1.0065 |
155
+ | No log | 4.6222 | 208 | 0.8069 | 0.2413 | 0.8069 | 0.8983 |
156
+ | No log | 4.6667 | 210 | 0.9162 | 0.0827 | 0.9162 | 0.9572 |
157
+ | No log | 4.7111 | 212 | 0.9253 | 0.1158 | 0.9253 | 0.9619 |
158
+ | No log | 4.7556 | 214 | 0.8177 | 0.1797 | 0.8177 | 0.9043 |
159
+ | No log | 4.8 | 216 | 0.8490 | 0.2383 | 0.8490 | 0.9214 |
160
+ | No log | 4.8444 | 218 | 0.9155 | 0.2697 | 0.9155 | 0.9568 |
161
+ | No log | 4.8889 | 220 | 0.8658 | 0.2692 | 0.8658 | 0.9305 |
162
+ | No log | 4.9333 | 222 | 0.8416 | 0.2943 | 0.8416 | 0.9174 |
163
+ | No log | 4.9778 | 224 | 0.8430 | 0.2717 | 0.8430 | 0.9182 |
164
+ | No log | 5.0222 | 226 | 0.8497 | 0.1015 | 0.8497 | 0.9218 |
165
+ | No log | 5.0667 | 228 | 0.8501 | 0.0734 | 0.8501 | 0.9220 |
166
+ | No log | 5.1111 | 230 | 0.8537 | 0.3011 | 0.8537 | 0.9240 |
167
+ | No log | 5.1556 | 232 | 0.8925 | 0.2780 | 0.8925 | 0.9447 |
168
+ | No log | 5.2 | 234 | 0.9080 | 0.2980 | 0.9080 | 0.9529 |
169
+ | No log | 5.2444 | 236 | 0.9276 | 0.2019 | 0.9276 | 0.9631 |
170
+ | No log | 5.2889 | 238 | 0.9403 | 0.2535 | 0.9403 | 0.9697 |
171
+ | No log | 5.3333 | 240 | 0.9574 | 0.2920 | 0.9574 | 0.9785 |
172
+ | No log | 5.3778 | 242 | 1.0040 | 0.2192 | 1.0040 | 1.0020 |
173
+ | No log | 5.4222 | 244 | 0.9976 | 0.2424 | 0.9976 | 0.9988 |
174
+ | No log | 5.4667 | 246 | 0.9249 | 0.2544 | 0.9249 | 0.9617 |
175
+ | No log | 5.5111 | 248 | 0.8690 | 0.2535 | 0.8690 | 0.9322 |
176
+ | No log | 5.5556 | 250 | 0.8672 | 0.1440 | 0.8672 | 0.9312 |
177
+ | No log | 5.6 | 252 | 0.8371 | 0.1440 | 0.8371 | 0.9149 |
178
+ | No log | 5.6444 | 254 | 0.8001 | 0.2386 | 0.8001 | 0.8945 |
179
+ | No log | 5.6889 | 256 | 0.8385 | 0.3763 | 0.8385 | 0.9157 |
180
+ | No log | 5.7333 | 258 | 0.8415 | 0.3763 | 0.8415 | 0.9173 |
181
+ | No log | 5.7778 | 260 | 0.8120 | 0.2413 | 0.8120 | 0.9011 |
182
+ | No log | 5.8222 | 262 | 0.8257 | 0.1741 | 0.8257 | 0.9087 |
183
+ | No log | 5.8667 | 264 | 0.8571 | 0.1206 | 0.8571 | 0.9258 |
184
+ | No log | 5.9111 | 266 | 0.8201 | 0.0727 | 0.8201 | 0.9056 |
185
+ | No log | 5.9556 | 268 | 0.7976 | 0.2413 | 0.7976 | 0.8931 |
186
+ | No log | 6.0 | 270 | 0.7883 | 0.2413 | 0.7883 | 0.8879 |
187
+ | No log | 6.0444 | 272 | 0.7834 | 0.0661 | 0.7834 | 0.8851 |
188
+ | No log | 6.0889 | 274 | 0.7889 | 0.0330 | 0.7889 | 0.8882 |
189
+ | No log | 6.1333 | 276 | 0.7928 | -0.0047 | 0.7928 | 0.8904 |
190
+ | No log | 6.1778 | 278 | 0.7832 | 0.2023 | 0.7832 | 0.8850 |
191
+ | No log | 6.2222 | 280 | 0.8010 | 0.2413 | 0.8010 | 0.8950 |
192
+ | No log | 6.2667 | 282 | 0.8093 | 0.2023 | 0.8093 | 0.8996 |
193
+ | No log | 6.3111 | 284 | 0.8069 | 0.1710 | 0.8069 | 0.8983 |
194
+ | No log | 6.3556 | 286 | 0.8097 | 0.1697 | 0.8097 | 0.8998 |
195
+ | No log | 6.4 | 288 | 0.8373 | 0.2215 | 0.8373 | 0.9150 |
196
+ | No log | 6.4444 | 290 | 0.9312 | 0.2375 | 0.9312 | 0.9650 |
197
+ | No log | 6.4889 | 292 | 0.9405 | 0.2375 | 0.9405 | 0.9698 |
198
+ | No log | 6.5333 | 294 | 0.8920 | 0.1945 | 0.8920 | 0.9445 |
199
+ | No log | 6.5778 | 296 | 0.8906 | 0.3400 | 0.8906 | 0.9437 |
200
+ | No log | 6.6222 | 298 | 0.8896 | 0.1089 | 0.8896 | 0.9432 |
201
+ | No log | 6.6667 | 300 | 0.8805 | 0.0818 | 0.8805 | 0.9384 |
202
+ | No log | 6.7111 | 302 | 0.8196 | 0.1052 | 0.8196 | 0.9053 |
203
+ | No log | 6.7556 | 304 | 0.7960 | 0.2717 | 0.7960 | 0.8922 |
204
+ | No log | 6.8 | 306 | 0.8354 | 0.2843 | 0.8354 | 0.9140 |
205
+ | No log | 6.8444 | 308 | 0.8613 | 0.2780 | 0.8613 | 0.9281 |
206
+ | No log | 6.8889 | 310 | 0.8387 | 0.2652 | 0.8387 | 0.9158 |
207
+ | No log | 6.9333 | 312 | 0.8455 | 0.2652 | 0.8455 | 0.9195 |
208
+ | No log | 6.9778 | 314 | 0.8352 | 0.2652 | 0.8352 | 0.9139 |
209
+ | No log | 7.0222 | 316 | 0.8267 | 0.2717 | 0.8267 | 0.9092 |
210
+ | No log | 7.0667 | 318 | 0.8381 | 0.2717 | 0.8381 | 0.9155 |
211
+ | No log | 7.1111 | 320 | 0.8385 | 0.2907 | 0.8385 | 0.9157 |
212
+ | No log | 7.1556 | 322 | 0.8469 | 0.2749 | 0.8469 | 0.9203 |
213
+ | No log | 7.2 | 324 | 0.8357 | 0.2749 | 0.8357 | 0.9142 |
214
+ | No log | 7.2444 | 326 | 0.8190 | 0.2749 | 0.8190 | 0.9050 |
215
+ | No log | 7.2889 | 328 | 0.7868 | 0.2717 | 0.7868 | 0.8870 |
216
+ | No log | 7.3333 | 330 | 0.7742 | 0.1723 | 0.7742 | 0.8799 |
217
+ | No log | 7.3778 | 332 | 0.7460 | 0.1723 | 0.7460 | 0.8637 |
218
+ | No log | 7.4222 | 334 | 0.7380 | 0.1723 | 0.7380 | 0.8591 |
219
+ | No log | 7.4667 | 336 | 0.7414 | 0.2043 | 0.7414 | 0.8611 |
220
+ | No log | 7.5111 | 338 | 0.7296 | 0.1723 | 0.7296 | 0.8542 |
221
+ | No log | 7.5556 | 340 | 0.7305 | 0.1723 | 0.7305 | 0.8547 |
222
+ | No log | 7.6 | 342 | 0.7452 | 0.1341 | 0.7452 | 0.8632 |
223
+ | No log | 7.6444 | 344 | 0.7530 | 0.1386 | 0.7530 | 0.8678 |
224
+ | No log | 7.6889 | 346 | 0.7549 | 0.1386 | 0.7549 | 0.8689 |
225
+ | No log | 7.7333 | 348 | 0.7819 | 0.2043 | 0.7819 | 0.8843 |
226
+ | No log | 7.7778 | 350 | 0.8589 | 0.3382 | 0.8589 | 0.9268 |
227
+ | No log | 7.8222 | 352 | 0.8741 | 0.3382 | 0.8741 | 0.9349 |
228
+ | No log | 7.8667 | 354 | 0.8271 | 0.1661 | 0.8271 | 0.9095 |
229
+ | No log | 7.9111 | 356 | 0.8115 | 0.1341 | 0.8115 | 0.9009 |
230
+ | No log | 7.9556 | 358 | 0.8214 | 0.1723 | 0.8214 | 0.9063 |
231
+ | No log | 8.0 | 360 | 0.8938 | 0.3020 | 0.8938 | 0.9454 |
232
+ | No log | 8.0444 | 362 | 0.9749 | 0.3099 | 0.9749 | 0.9874 |
233
+ | No log | 8.0889 | 364 | 0.9290 | 0.3238 | 0.9290 | 0.9638 |
234
+ | No log | 8.1333 | 366 | 0.8646 | 0.2652 | 0.8646 | 0.9299 |
235
+ | No log | 8.1778 | 368 | 0.8981 | 0.2943 | 0.8981 | 0.9477 |
236
+ | No log | 8.2222 | 370 | 0.9783 | 0.2887 | 0.9783 | 0.9891 |
237
+ | No log | 8.2667 | 372 | 0.9933 | 0.2832 | 0.9933 | 0.9966 |
238
+ | No log | 8.3111 | 374 | 0.9365 | 0.2887 | 0.9365 | 0.9677 |
239
+ | No log | 8.3556 | 376 | 0.8384 | 0.3051 | 0.8384 | 0.9157 |
240
+ | No log | 8.4 | 378 | 0.7855 | 0.2717 | 0.7855 | 0.8863 |
241
+ | No log | 8.4444 | 380 | 0.7827 | 0.2379 | 0.7827 | 0.8847 |
242
+ | No log | 8.4889 | 382 | 0.8240 | 0.3238 | 0.8240 | 0.9077 |
243
+ | No log | 8.5333 | 384 | 0.8896 | 0.3234 | 0.8896 | 0.9432 |
244
+ | No log | 8.5778 | 386 | 0.8639 | 0.3099 | 0.8639 | 0.9294 |
245
+ | No log | 8.6222 | 388 | 0.7837 | 0.2950 | 0.7837 | 0.8853 |
246
+ | No log | 8.6667 | 390 | 0.7718 | 0.2379 | 0.7718 | 0.8785 |
247
+ | No log | 8.7111 | 392 | 0.8280 | 0.2847 | 0.8280 | 0.9099 |
248
+ | No log | 8.7556 | 394 | 1.0078 | 0.2569 | 1.0078 | 1.0039 |
249
+ | No log | 8.8 | 396 | 1.0513 | 0.2406 | 1.0513 | 1.0253 |
250
+ | No log | 8.8444 | 398 | 0.9210 | 0.2823 | 0.9210 | 0.9597 |
251
+ | No log | 8.8889 | 400 | 0.7839 | 0.2270 | 0.7839 | 0.8854 |
252
+ | No log | 8.9333 | 402 | 0.7602 | 0.2591 | 0.7602 | 0.8719 |
253
+ | No log | 8.9778 | 404 | 0.7595 | 0.2652 | 0.7595 | 0.8715 |
254
+ | No log | 9.0222 | 406 | 0.7717 | 0.2270 | 0.7717 | 0.8784 |
255
+ | No log | 9.0667 | 408 | 0.8118 | 0.3155 | 0.8118 | 0.9010 |
256
+ | No log | 9.1111 | 410 | 0.8169 | 0.3399 | 0.8169 | 0.9038 |
257
+ | No log | 9.1556 | 412 | 0.7661 | 0.2981 | 0.7661 | 0.8753 |
258
+ | No log | 9.2 | 414 | 0.7217 | 0.2063 | 0.7217 | 0.8495 |
259
+ | No log | 9.2444 | 416 | 0.7284 | 0.2787 | 0.7284 | 0.8534 |
260
+ | No log | 9.2889 | 418 | 0.8135 | 0.3444 | 0.8135 | 0.9020 |
261
+ | No log | 9.3333 | 420 | 0.8713 | 0.3712 | 0.8713 | 0.9334 |
262
+ | No log | 9.3778 | 422 | 0.9817 | 0.2781 | 0.9817 | 0.9908 |
263
+ | No log | 9.4222 | 424 | 1.0481 | 0.2636 | 1.0481 | 1.0237 |
264
+ | No log | 9.4667 | 426 | 1.0152 | 0.2200 | 1.0152 | 1.0076 |
265
+ | No log | 9.5111 | 428 | 0.9086 | 0.3268 | 0.9086 | 0.9532 |
266
+ | No log | 9.5556 | 430 | 0.8122 | 0.2270 | 0.8122 | 0.9012 |
267
+ | No log | 9.6 | 432 | 0.8200 | 0.2564 | 0.8200 | 0.9056 |
268
+ | No log | 9.6444 | 434 | 0.8248 | 0.2256 | 0.8248 | 0.9082 |
269
+ | No log | 9.6889 | 436 | 0.8474 | 0.2943 | 0.8474 | 0.9205 |
270
+ | No log | 9.7333 | 438 | 0.9539 | 0.2124 | 0.9539 | 0.9767 |
271
+ | No log | 9.7778 | 440 | 1.0177 | 0.2076 | 1.0177 | 1.0088 |
272
+ | No log | 9.8222 | 442 | 1.0099 | 0.2076 | 1.0099 | 1.0049 |
273
+ | No log | 9.8667 | 444 | 0.9938 | 0.2076 | 0.9938 | 0.9969 |
274
+ | No log | 9.9111 | 446 | 0.8961 | 0.2847 | 0.8961 | 0.9466 |
275
+ | No log | 9.9556 | 448 | 0.8565 | 0.2319 | 0.8565 | 0.9255 |
276
+ | No log | 10.0 | 450 | 0.8787 | 0.2261 | 0.8787 | 0.9374 |
277
+ | No log | 10.0444 | 452 | 0.9808 | 0.3169 | 0.9808 | 0.9903 |
278
+ | No log | 10.0889 | 454 | 1.0597 | 0.2510 | 1.0597 | 1.0294 |
279
+ | No log | 10.1333 | 456 | 1.0098 | 0.3359 | 1.0098 | 1.0049 |
280
+ | No log | 10.1778 | 458 | 0.8895 | 0.3950 | 0.8895 | 0.9431 |
281
+ | No log | 10.2222 | 460 | 0.8021 | 0.1400 | 0.8021 | 0.8956 |
282
+ | No log | 10.2667 | 462 | 0.7884 | 0.1050 | 0.7884 | 0.8879 |
283
+ | No log | 10.3111 | 464 | 0.7912 | 0.1353 | 0.7912 | 0.8895 |
284
+ | No log | 10.3556 | 466 | 0.8424 | 0.3267 | 0.8424 | 0.9179 |
285
+ | No log | 10.4 | 468 | 0.9965 | 0.3294 | 0.9965 | 0.9983 |
286
+ | No log | 10.4444 | 470 | 1.1197 | 0.2612 | 1.1197 | 1.0581 |
287
+ | No log | 10.4889 | 472 | 1.1011 | 0.2439 | 1.1011 | 1.0494 |
288
+ | No log | 10.5333 | 474 | 0.9410 | 0.2949 | 0.9410 | 0.9700 |
289
+ | No log | 10.5778 | 476 | 0.8311 | 0.2981 | 0.8311 | 0.9117 |
290
+ | No log | 10.6222 | 478 | 0.8335 | 0.2038 | 0.8335 | 0.9130 |
291
+ | No log | 10.6667 | 480 | 0.8537 | 0.1091 | 0.8537 | 0.9240 |
292
+ | No log | 10.7111 | 482 | 0.8251 | 0.1733 | 0.8251 | 0.9084 |
293
+ | No log | 10.7556 | 484 | 0.7997 | 0.2043 | 0.7997 | 0.8943 |
294
+ | No log | 10.8 | 486 | 0.8176 | 0.2877 | 0.8176 | 0.9042 |
295
+ | No log | 10.8444 | 488 | 0.8584 | 0.2960 | 0.8584 | 0.9265 |
296
+ | No log | 10.8889 | 490 | 0.8516 | 0.3312 | 0.8516 | 0.9228 |
297
+ | No log | 10.9333 | 492 | 0.8086 | 0.3387 | 0.8086 | 0.8992 |
298
+ | No log | 10.9778 | 494 | 0.7660 | 0.1353 | 0.7660 | 0.8752 |
299
+ | No log | 11.0222 | 496 | 0.7617 | 0.1353 | 0.7617 | 0.8728 |
300
+ | No log | 11.0667 | 498 | 0.7839 | 0.2981 | 0.7839 | 0.8854 |
301
+ | 0.3506 | 11.1111 | 500 | 0.8360 | 0.3023 | 0.8360 | 0.9143 |
302
+ | 0.3506 | 11.1556 | 502 | 0.8539 | 0.2866 | 0.8539 | 0.9241 |
303
+ | 0.3506 | 11.2 | 504 | 0.8231 | 0.3155 | 0.8231 | 0.9072 |
304
+ | 0.3506 | 11.2444 | 506 | 0.7844 | 0.2981 | 0.7844 | 0.8857 |
305
+ | 0.3506 | 11.2889 | 508 | 0.7601 | 0.2063 | 0.7601 | 0.8718 |
306
+ | 0.3506 | 11.3333 | 510 | 0.7506 | 0.2063 | 0.7506 | 0.8664 |
307
+ | 0.3506 | 11.3778 | 512 | 0.7577 | 0.2379 | 0.7577 | 0.8705 |
308
+ | 0.3506 | 11.4222 | 514 | 0.7828 | 0.3387 | 0.7828 | 0.8847 |
309
+ | 0.3506 | 11.4667 | 516 | 0.7894 | 0.3387 | 0.7894 | 0.8885 |
310
+ | 0.3506 | 11.5111 | 518 | 0.7666 | 0.2685 | 0.7666 | 0.8755 |
311
+ | 0.3506 | 11.5556 | 520 | 0.7425 | 0.2063 | 0.7425 | 0.8617 |
312
+ | 0.3506 | 11.6 | 522 | 0.7336 | 0.2063 | 0.7336 | 0.8565 |
313
+ | 0.3506 | 11.6444 | 524 | 0.7384 | 0.2063 | 0.7384 | 0.8593 |
314
+ | 0.3506 | 11.6889 | 526 | 0.7500 | 0.2685 | 0.7500 | 0.8660 |
315
+
316
+
317
+ ### Framework versions
318
+
319
+ - Transformers 4.44.2
320
+ - Pytorch 2.4.0+cu118
321
+ - Datasets 2.21.0
322
+ - 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 sha256:26dece102547c6605a0622ad82eb76e7606fa280fa1dbf4e42fbf80fb5afb6e7
3
+ size 540799996
training_args.bin ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:07d3f1b89d2fe97edfe526cba6bf2a122fb61e6fbec25e42ba967f2f0d9979d5
3
+ size 5368