MayBashendy commited on
Commit
60533dc
·
verified ·
1 Parent(s): 3317793

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_B_usingWellWrittenEssays_FineTuningAraBERT_run2_AugV5_k12_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_k12_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: 0.7869
19
+ - Qwk: 0.5726
20
+ - Mse: 0.7869
21
+ - Rmse: 0.8871
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 | 0.0308 | 2 | 4.6696 | -0.0132 | 4.6696 | 2.1609 |
53
+ | No log | 0.0615 | 4 | 2.9418 | -0.0622 | 2.9418 | 1.7152 |
54
+ | No log | 0.0923 | 6 | 1.9098 | -0.0233 | 1.9098 | 1.3820 |
55
+ | No log | 0.1231 | 8 | 1.6279 | 0.1115 | 1.6279 | 1.2759 |
56
+ | No log | 0.1538 | 10 | 1.2993 | 0.1576 | 1.2993 | 1.1399 |
57
+ | No log | 0.1846 | 12 | 1.2187 | 0.0872 | 1.2187 | 1.1040 |
58
+ | No log | 0.2154 | 14 | 1.2841 | 0.0206 | 1.2841 | 1.1332 |
59
+ | No log | 0.2462 | 16 | 1.3591 | -0.0040 | 1.3591 | 1.1658 |
60
+ | No log | 0.2769 | 18 | 1.3209 | 0.0370 | 1.3209 | 1.1493 |
61
+ | No log | 0.3077 | 20 | 1.2797 | 0.0107 | 1.2797 | 1.1312 |
62
+ | No log | 0.3385 | 22 | 1.2792 | 0.0516 | 1.2792 | 1.1310 |
63
+ | No log | 0.3692 | 24 | 1.3305 | 0.0573 | 1.3305 | 1.1535 |
64
+ | No log | 0.4 | 26 | 1.3757 | 0.0342 | 1.3757 | 1.1729 |
65
+ | No log | 0.4308 | 28 | 1.4115 | 0.1016 | 1.4115 | 1.1881 |
66
+ | No log | 0.4615 | 30 | 1.4138 | 0.1136 | 1.4138 | 1.1890 |
67
+ | No log | 0.4923 | 32 | 1.5669 | 0.1427 | 1.5669 | 1.2517 |
68
+ | No log | 0.5231 | 34 | 1.5126 | 0.1138 | 1.5126 | 1.2299 |
69
+ | No log | 0.5538 | 36 | 1.4518 | 0.1784 | 1.4518 | 1.2049 |
70
+ | No log | 0.5846 | 38 | 1.2857 | 0.0731 | 1.2857 | 1.1339 |
71
+ | No log | 0.6154 | 40 | 1.2986 | 0.1267 | 1.2986 | 1.1395 |
72
+ | No log | 0.6462 | 42 | 1.3013 | 0.1576 | 1.3013 | 1.1407 |
73
+ | No log | 0.6769 | 44 | 1.2741 | 0.1111 | 1.2741 | 1.1287 |
74
+ | No log | 0.7077 | 46 | 1.2291 | 0.2016 | 1.2291 | 1.1087 |
75
+ | No log | 0.7385 | 48 | 1.2823 | 0.2319 | 1.2823 | 1.1324 |
76
+ | No log | 0.7692 | 50 | 1.3963 | 0.1446 | 1.3963 | 1.1817 |
77
+ | No log | 0.8 | 52 | 1.5202 | 0.0808 | 1.5202 | 1.2330 |
78
+ | No log | 0.8308 | 54 | 1.7453 | -0.0480 | 1.7453 | 1.3211 |
79
+ | No log | 0.8615 | 56 | 1.4444 | 0.1331 | 1.4444 | 1.2018 |
80
+ | No log | 0.8923 | 58 | 1.1491 | 0.2625 | 1.1491 | 1.0719 |
81
+ | No log | 0.9231 | 60 | 1.0236 | 0.2887 | 1.0236 | 1.0117 |
82
+ | No log | 0.9538 | 62 | 0.9830 | 0.2731 | 0.9830 | 0.9914 |
83
+ | No log | 0.9846 | 64 | 0.9750 | 0.2731 | 0.9750 | 0.9874 |
84
+ | No log | 1.0154 | 66 | 0.9648 | 0.3421 | 0.9648 | 0.9822 |
85
+ | No log | 1.0462 | 68 | 0.9922 | 0.4198 | 0.9922 | 0.9961 |
86
+ | No log | 1.0769 | 70 | 0.9617 | 0.3042 | 0.9617 | 0.9807 |
87
+ | No log | 1.1077 | 72 | 1.0658 | 0.4072 | 1.0658 | 1.0324 |
88
+ | No log | 1.1385 | 74 | 1.0713 | 0.3941 | 1.0713 | 1.0350 |
89
+ | No log | 1.1692 | 76 | 0.9388 | 0.3454 | 0.9388 | 0.9689 |
90
+ | No log | 1.2 | 78 | 1.1819 | 0.3557 | 1.1819 | 1.0872 |
91
+ | No log | 1.2308 | 80 | 1.4622 | 0.3098 | 1.4622 | 1.2092 |
92
+ | No log | 1.2615 | 82 | 1.3211 | 0.3462 | 1.3211 | 1.1494 |
93
+ | No log | 1.2923 | 84 | 1.0310 | 0.3855 | 1.0310 | 1.0154 |
94
+ | No log | 1.3231 | 86 | 0.9728 | 0.3371 | 0.9728 | 0.9863 |
95
+ | No log | 1.3538 | 88 | 1.1067 | 0.3160 | 1.1067 | 1.0520 |
96
+ | No log | 1.3846 | 90 | 1.2586 | 0.1490 | 1.2586 | 1.1219 |
97
+ | No log | 1.4154 | 92 | 1.1226 | 0.2231 | 1.1226 | 1.0595 |
98
+ | No log | 1.4462 | 94 | 0.9214 | 0.3616 | 0.9214 | 0.9599 |
99
+ | No log | 1.4769 | 96 | 0.9243 | 0.4158 | 0.9243 | 0.9614 |
100
+ | No log | 1.5077 | 98 | 0.9187 | 0.4498 | 0.9187 | 0.9585 |
101
+ | No log | 1.5385 | 100 | 0.9283 | 0.5014 | 0.9283 | 0.9635 |
102
+ | No log | 1.5692 | 102 | 1.1087 | 0.4625 | 1.1087 | 1.0529 |
103
+ | No log | 1.6 | 104 | 1.0972 | 0.4217 | 1.0972 | 1.0475 |
104
+ | No log | 1.6308 | 106 | 0.9155 | 0.5192 | 0.9155 | 0.9568 |
105
+ | No log | 1.6615 | 108 | 0.8530 | 0.5274 | 0.8530 | 0.9236 |
106
+ | No log | 1.6923 | 110 | 0.8221 | 0.5274 | 0.8221 | 0.9067 |
107
+ | No log | 1.7231 | 112 | 0.9014 | 0.4454 | 0.9014 | 0.9494 |
108
+ | No log | 1.7538 | 114 | 1.1243 | 0.2955 | 1.1243 | 1.0603 |
109
+ | No log | 1.7846 | 116 | 1.1565 | 0.3072 | 1.1565 | 1.0754 |
110
+ | No log | 1.8154 | 118 | 0.9445 | 0.3931 | 0.9445 | 0.9719 |
111
+ | No log | 1.8462 | 120 | 0.8587 | 0.4261 | 0.8587 | 0.9267 |
112
+ | No log | 1.8769 | 122 | 0.8498 | 0.4599 | 0.8498 | 0.9218 |
113
+ | No log | 1.9077 | 124 | 0.9034 | 0.4434 | 0.9034 | 0.9505 |
114
+ | No log | 1.9385 | 126 | 1.0222 | 0.4 | 1.0222 | 1.0111 |
115
+ | No log | 1.9692 | 128 | 0.9521 | 0.4031 | 0.9521 | 0.9758 |
116
+ | No log | 2.0 | 130 | 0.9061 | 0.4711 | 0.9061 | 0.9519 |
117
+ | No log | 2.0308 | 132 | 0.8957 | 0.4219 | 0.8957 | 0.9464 |
118
+ | No log | 2.0615 | 134 | 0.9232 | 0.3969 | 0.9232 | 0.9609 |
119
+ | No log | 2.0923 | 136 | 0.9303 | 0.4140 | 0.9303 | 0.9645 |
120
+ | No log | 2.1231 | 138 | 0.8857 | 0.3938 | 0.8857 | 0.9411 |
121
+ | No log | 2.1538 | 140 | 0.8828 | 0.4620 | 0.8828 | 0.9396 |
122
+ | No log | 2.1846 | 142 | 0.8567 | 0.4430 | 0.8567 | 0.9256 |
123
+ | No log | 2.2154 | 144 | 0.8666 | 0.4934 | 0.8666 | 0.9309 |
124
+ | No log | 2.2462 | 146 | 0.8722 | 0.4477 | 0.8722 | 0.9339 |
125
+ | No log | 2.2769 | 148 | 0.8458 | 0.4704 | 0.8458 | 0.9197 |
126
+ | No log | 2.3077 | 150 | 0.8106 | 0.4628 | 0.8106 | 0.9003 |
127
+ | No log | 2.3385 | 152 | 0.8367 | 0.5180 | 0.8367 | 0.9147 |
128
+ | No log | 2.3692 | 154 | 0.8103 | 0.5591 | 0.8103 | 0.9001 |
129
+ | No log | 2.4 | 156 | 0.7838 | 0.4415 | 0.7838 | 0.8853 |
130
+ | No log | 2.4308 | 158 | 0.7961 | 0.5591 | 0.7961 | 0.8923 |
131
+ | No log | 2.4615 | 160 | 0.7923 | 0.5255 | 0.7923 | 0.8901 |
132
+ | No log | 2.4923 | 162 | 0.7865 | 0.5255 | 0.7865 | 0.8869 |
133
+ | No log | 2.5231 | 164 | 0.7829 | 0.4946 | 0.7829 | 0.8848 |
134
+ | No log | 2.5538 | 166 | 0.8783 | 0.4415 | 0.8783 | 0.9372 |
135
+ | No log | 2.5846 | 168 | 0.8652 | 0.4537 | 0.8652 | 0.9301 |
136
+ | No log | 2.6154 | 170 | 0.7676 | 0.5126 | 0.7676 | 0.8761 |
137
+ | No log | 2.6462 | 172 | 1.0155 | 0.5207 | 1.0155 | 1.0077 |
138
+ | No log | 2.6769 | 174 | 1.0121 | 0.5419 | 1.0121 | 1.0060 |
139
+ | No log | 2.7077 | 176 | 0.7876 | 0.5484 | 0.7876 | 0.8874 |
140
+ | No log | 2.7385 | 178 | 0.8158 | 0.4991 | 0.8158 | 0.9032 |
141
+ | No log | 2.7692 | 180 | 0.8069 | 0.4861 | 0.8069 | 0.8983 |
142
+ | No log | 2.8 | 182 | 0.8035 | 0.5059 | 0.8035 | 0.8964 |
143
+ | No log | 2.8308 | 184 | 0.9426 | 0.4606 | 0.9426 | 0.9709 |
144
+ | No log | 2.8615 | 186 | 0.9830 | 0.4572 | 0.9830 | 0.9915 |
145
+ | No log | 2.8923 | 188 | 0.8272 | 0.4948 | 0.8272 | 0.9095 |
146
+ | No log | 2.9231 | 190 | 0.8140 | 0.4888 | 0.8140 | 0.9022 |
147
+ | No log | 2.9538 | 192 | 0.7977 | 0.5455 | 0.7977 | 0.8932 |
148
+ | No log | 2.9846 | 194 | 0.8825 | 0.4631 | 0.8825 | 0.9394 |
149
+ | No log | 3.0154 | 196 | 1.2143 | 0.4004 | 1.2143 | 1.1020 |
150
+ | No log | 3.0462 | 198 | 1.3561 | 0.3626 | 1.3561 | 1.1645 |
151
+ | No log | 3.0769 | 200 | 1.1302 | 0.4332 | 1.1302 | 1.0631 |
152
+ | No log | 3.1077 | 202 | 0.8343 | 0.4902 | 0.8343 | 0.9134 |
153
+ | No log | 3.1385 | 204 | 0.7742 | 0.4760 | 0.7742 | 0.8799 |
154
+ | No log | 3.1692 | 206 | 0.7866 | 0.5287 | 0.7866 | 0.8869 |
155
+ | No log | 3.2 | 208 | 0.7795 | 0.5291 | 0.7795 | 0.8829 |
156
+ | No log | 3.2308 | 210 | 0.7915 | 0.5466 | 0.7915 | 0.8897 |
157
+ | No log | 3.2615 | 212 | 0.7985 | 0.5137 | 0.7985 | 0.8936 |
158
+ | No log | 3.2923 | 214 | 0.8140 | 0.5137 | 0.8140 | 0.9022 |
159
+ | No log | 3.3231 | 216 | 0.8391 | 0.5583 | 0.8391 | 0.9160 |
160
+ | No log | 3.3538 | 218 | 1.0091 | 0.4401 | 1.0091 | 1.0045 |
161
+ | No log | 3.3846 | 220 | 1.3560 | 0.3426 | 1.3560 | 1.1645 |
162
+ | No log | 3.4154 | 222 | 1.2020 | 0.3934 | 1.2020 | 1.0964 |
163
+ | No log | 3.4462 | 224 | 0.8624 | 0.5165 | 0.8624 | 0.9287 |
164
+ | No log | 3.4769 | 226 | 0.8538 | 0.4835 | 0.8538 | 0.9240 |
165
+ | No log | 3.5077 | 228 | 0.8674 | 0.4846 | 0.8674 | 0.9314 |
166
+ | No log | 3.5385 | 230 | 0.8808 | 0.4846 | 0.8808 | 0.9385 |
167
+ | No log | 3.5692 | 232 | 0.8296 | 0.4889 | 0.8296 | 0.9108 |
168
+ | No log | 3.6 | 234 | 0.8236 | 0.5513 | 0.8236 | 0.9075 |
169
+ | No log | 3.6308 | 236 | 0.8260 | 0.4730 | 0.8260 | 0.9088 |
170
+ | No log | 3.6615 | 238 | 0.8066 | 0.5251 | 0.8066 | 0.8981 |
171
+ | No log | 3.6923 | 240 | 0.9127 | 0.5073 | 0.9127 | 0.9553 |
172
+ | No log | 3.7231 | 242 | 0.9677 | 0.5353 | 0.9677 | 0.9837 |
173
+ | No log | 3.7538 | 244 | 0.8758 | 0.5073 | 0.8758 | 0.9358 |
174
+ | No log | 3.7846 | 246 | 0.7804 | 0.5515 | 0.7804 | 0.8834 |
175
+ | No log | 3.8154 | 248 | 0.8011 | 0.4529 | 0.8011 | 0.8951 |
176
+ | No log | 3.8462 | 250 | 0.7806 | 0.4879 | 0.7806 | 0.8835 |
177
+ | No log | 3.8769 | 252 | 0.8494 | 0.5107 | 0.8494 | 0.9216 |
178
+ | No log | 3.9077 | 254 | 0.9234 | 0.5164 | 0.9234 | 0.9610 |
179
+ | No log | 3.9385 | 256 | 1.0195 | 0.5313 | 1.0195 | 1.0097 |
180
+ | No log | 3.9692 | 258 | 0.9800 | 0.5353 | 0.9800 | 0.9900 |
181
+ | No log | 4.0 | 260 | 0.8949 | 0.5164 | 0.8949 | 0.9460 |
182
+ | No log | 4.0308 | 262 | 0.7845 | 0.5059 | 0.7845 | 0.8857 |
183
+ | No log | 4.0615 | 264 | 0.8556 | 0.4741 | 0.8556 | 0.9250 |
184
+ | No log | 4.0923 | 266 | 0.8940 | 0.5126 | 0.8940 | 0.9455 |
185
+ | No log | 4.1231 | 268 | 0.8274 | 0.4772 | 0.8274 | 0.9096 |
186
+ | No log | 4.1538 | 270 | 0.8302 | 0.4534 | 0.8302 | 0.9112 |
187
+ | No log | 4.1846 | 272 | 0.9213 | 0.4983 | 0.9213 | 0.9598 |
188
+ | No log | 4.2154 | 274 | 0.9564 | 0.4983 | 0.9564 | 0.9779 |
189
+ | No log | 4.2462 | 276 | 0.9001 | 0.4275 | 0.9001 | 0.9487 |
190
+ | No log | 4.2769 | 278 | 0.8812 | 0.3715 | 0.8812 | 0.9387 |
191
+ | No log | 4.3077 | 280 | 0.8805 | 0.4125 | 0.8805 | 0.9383 |
192
+ | No log | 4.3385 | 282 | 0.9432 | 0.4998 | 0.9432 | 0.9712 |
193
+ | No log | 4.3692 | 284 | 1.0976 | 0.5056 | 1.0976 | 1.0477 |
194
+ | No log | 4.4 | 286 | 1.2059 | 0.4215 | 1.2059 | 1.0981 |
195
+ | No log | 4.4308 | 288 | 1.1172 | 0.5098 | 1.1172 | 1.0570 |
196
+ | No log | 4.4615 | 290 | 0.9691 | 0.5114 | 0.9691 | 0.9844 |
197
+ | No log | 4.4923 | 292 | 0.9232 | 0.3554 | 0.9232 | 0.9608 |
198
+ | No log | 4.5231 | 294 | 0.9380 | 0.3541 | 0.9380 | 0.9685 |
199
+ | No log | 4.5538 | 296 | 0.9386 | 0.3326 | 0.9386 | 0.9688 |
200
+ | No log | 4.5846 | 298 | 1.0004 | 0.3864 | 1.0004 | 1.0002 |
201
+ | No log | 4.6154 | 300 | 1.0313 | 0.3367 | 1.0313 | 1.0155 |
202
+ | No log | 4.6462 | 302 | 1.0173 | 0.3996 | 1.0173 | 1.0086 |
203
+ | No log | 4.6769 | 304 | 0.9582 | 0.4966 | 0.9582 | 0.9789 |
204
+ | No log | 4.7077 | 306 | 0.8833 | 0.4820 | 0.8833 | 0.9398 |
205
+ | No log | 4.7385 | 308 | 0.8514 | 0.4290 | 0.8514 | 0.9227 |
206
+ | No log | 4.7692 | 310 | 0.8428 | 0.3969 | 0.8428 | 0.9180 |
207
+ | No log | 4.8 | 312 | 0.8382 | 0.4637 | 0.8382 | 0.9155 |
208
+ | No log | 4.8308 | 314 | 0.8839 | 0.4337 | 0.8839 | 0.9401 |
209
+ | No log | 4.8615 | 316 | 0.8405 | 0.4637 | 0.8405 | 0.9168 |
210
+ | No log | 4.8923 | 318 | 0.8192 | 0.4608 | 0.8192 | 0.9051 |
211
+ | No log | 4.9231 | 320 | 0.8008 | 0.4874 | 0.8008 | 0.8949 |
212
+ | No log | 4.9538 | 322 | 0.7903 | 0.5011 | 0.7903 | 0.8890 |
213
+ | No log | 4.9846 | 324 | 0.7919 | 0.4902 | 0.7919 | 0.8899 |
214
+ | No log | 5.0154 | 326 | 0.7857 | 0.5056 | 0.7857 | 0.8864 |
215
+ | No log | 5.0462 | 328 | 0.7874 | 0.5058 | 0.7874 | 0.8874 |
216
+ | No log | 5.0769 | 330 | 0.7904 | 0.4575 | 0.7904 | 0.8890 |
217
+ | No log | 5.1077 | 332 | 0.7973 | 0.4381 | 0.7973 | 0.8929 |
218
+ | No log | 5.1385 | 334 | 0.7933 | 0.4482 | 0.7933 | 0.8907 |
219
+ | No log | 5.1692 | 336 | 0.7889 | 0.4711 | 0.7889 | 0.8882 |
220
+ | No log | 5.2 | 338 | 0.7937 | 0.4603 | 0.7937 | 0.8909 |
221
+ | No log | 5.2308 | 340 | 0.7662 | 0.5534 | 0.7662 | 0.8753 |
222
+ | No log | 5.2615 | 342 | 0.8107 | 0.4536 | 0.8107 | 0.9004 |
223
+ | No log | 5.2923 | 344 | 0.8558 | 0.4410 | 0.8558 | 0.9251 |
224
+ | No log | 5.3231 | 346 | 0.7999 | 0.4975 | 0.7999 | 0.8944 |
225
+ | No log | 5.3538 | 348 | 0.7754 | 0.5381 | 0.7754 | 0.8805 |
226
+ | No log | 5.3846 | 350 | 0.8243 | 0.4808 | 0.8243 | 0.9079 |
227
+ | No log | 5.4154 | 352 | 0.8711 | 0.4775 | 0.8711 | 0.9333 |
228
+ | No log | 5.4462 | 354 | 0.8374 | 0.4931 | 0.8374 | 0.9151 |
229
+ | No log | 5.4769 | 356 | 0.8237 | 0.3615 | 0.8237 | 0.9076 |
230
+ | No log | 5.5077 | 358 | 0.8849 | 0.4155 | 0.8849 | 0.9407 |
231
+ | No log | 5.5385 | 360 | 0.9046 | 0.4155 | 0.9046 | 0.9511 |
232
+ | No log | 5.5692 | 362 | 0.8614 | 0.3942 | 0.8614 | 0.9281 |
233
+ | No log | 5.6 | 364 | 0.8499 | 0.4611 | 0.8499 | 0.9219 |
234
+ | No log | 5.6308 | 366 | 0.9414 | 0.5060 | 0.9414 | 0.9702 |
235
+ | No log | 5.6615 | 368 | 0.9742 | 0.4938 | 0.9742 | 0.9870 |
236
+ | No log | 5.6923 | 370 | 0.9120 | 0.4799 | 0.9120 | 0.9550 |
237
+ | No log | 5.7231 | 372 | 0.8738 | 0.3890 | 0.8738 | 0.9347 |
238
+ | No log | 5.7538 | 374 | 0.8933 | 0.4406 | 0.8933 | 0.9451 |
239
+ | No log | 5.7846 | 376 | 0.9341 | 0.4310 | 0.9341 | 0.9665 |
240
+ | No log | 5.8154 | 378 | 0.9321 | 0.4310 | 0.9321 | 0.9654 |
241
+ | No log | 5.8462 | 380 | 0.8736 | 0.4606 | 0.8736 | 0.9346 |
242
+ | No log | 5.8769 | 382 | 0.8462 | 0.5308 | 0.8462 | 0.9199 |
243
+ | No log | 5.9077 | 384 | 0.9271 | 0.4954 | 0.9271 | 0.9629 |
244
+ | No log | 5.9385 | 386 | 0.9734 | 0.5236 | 0.9734 | 0.9866 |
245
+ | No log | 5.9692 | 388 | 0.9392 | 0.5044 | 0.9392 | 0.9691 |
246
+ | No log | 6.0 | 390 | 0.8649 | 0.4714 | 0.8649 | 0.9300 |
247
+ | No log | 6.0308 | 392 | 0.8374 | 0.4902 | 0.8374 | 0.9151 |
248
+ | No log | 6.0615 | 394 | 0.8307 | 0.5026 | 0.8307 | 0.9114 |
249
+ | No log | 6.0923 | 396 | 0.8422 | 0.4676 | 0.8422 | 0.9177 |
250
+ | No log | 6.1231 | 398 | 0.8480 | 0.4902 | 0.8480 | 0.9209 |
251
+ | No log | 6.1538 | 400 | 0.8622 | 0.4676 | 0.8622 | 0.9285 |
252
+ | No log | 6.1846 | 402 | 0.8778 | 0.4676 | 0.8778 | 0.9369 |
253
+ | No log | 6.2154 | 404 | 0.8624 | 0.5262 | 0.8624 | 0.9287 |
254
+ | No log | 6.2462 | 406 | 0.8589 | 0.5058 | 0.8589 | 0.9268 |
255
+ | No log | 6.2769 | 408 | 0.8569 | 0.4617 | 0.8569 | 0.9257 |
256
+ | No log | 6.3077 | 410 | 0.8563 | 0.4159 | 0.8563 | 0.9254 |
257
+ | No log | 6.3385 | 412 | 0.8462 | 0.4643 | 0.8462 | 0.9199 |
258
+ | No log | 6.3692 | 414 | 0.8342 | 0.5058 | 0.8342 | 0.9133 |
259
+ | No log | 6.4 | 416 | 0.8379 | 0.4902 | 0.8379 | 0.9153 |
260
+ | No log | 6.4308 | 418 | 0.8536 | 0.4595 | 0.8536 | 0.9239 |
261
+ | No log | 6.4615 | 420 | 0.8586 | 0.4584 | 0.8586 | 0.9266 |
262
+ | No log | 6.4923 | 422 | 0.8434 | 0.3998 | 0.8434 | 0.9184 |
263
+ | No log | 6.5231 | 424 | 0.8243 | 0.3493 | 0.8243 | 0.9079 |
264
+ | No log | 6.5538 | 426 | 0.8243 | 0.4711 | 0.8243 | 0.9079 |
265
+ | No log | 6.5846 | 428 | 0.8214 | 0.5124 | 0.8214 | 0.9063 |
266
+ | No log | 6.6154 | 430 | 0.7866 | 0.5498 | 0.7866 | 0.8869 |
267
+ | No log | 6.6462 | 432 | 0.7911 | 0.5474 | 0.7911 | 0.8894 |
268
+ | No log | 6.6769 | 434 | 0.8853 | 0.5258 | 0.8853 | 0.9409 |
269
+ | No log | 6.7077 | 436 | 1.0723 | 0.5302 | 1.0723 | 1.0355 |
270
+ | No log | 6.7385 | 438 | 1.1532 | 0.5015 | 1.1532 | 1.0739 |
271
+ | No log | 6.7692 | 440 | 1.0413 | 0.4751 | 1.0413 | 1.0204 |
272
+ | No log | 6.8 | 442 | 0.9656 | 0.4583 | 0.9656 | 0.9826 |
273
+ | No log | 6.8308 | 444 | 0.8496 | 0.5291 | 0.8496 | 0.9218 |
274
+ | No log | 6.8615 | 446 | 0.8147 | 0.5220 | 0.8147 | 0.9026 |
275
+ | No log | 6.8923 | 448 | 0.8577 | 0.5291 | 0.8577 | 0.9261 |
276
+ | No log | 6.9231 | 450 | 0.9725 | 0.5160 | 0.9725 | 0.9862 |
277
+ | No log | 6.9538 | 452 | 1.0603 | 0.5091 | 1.0603 | 1.0297 |
278
+ | No log | 6.9846 | 454 | 1.1761 | 0.5115 | 1.1761 | 1.0845 |
279
+ | No log | 7.0154 | 456 | 1.2566 | 0.3937 | 1.2566 | 1.1210 |
280
+ | No log | 7.0462 | 458 | 1.1575 | 0.3826 | 1.1575 | 1.0759 |
281
+ | No log | 7.0769 | 460 | 1.0480 | 0.4168 | 1.0480 | 1.0237 |
282
+ | No log | 7.1077 | 462 | 0.9459 | 0.4829 | 0.9459 | 0.9726 |
283
+ | No log | 7.1385 | 464 | 0.9875 | 0.5054 | 0.9875 | 0.9937 |
284
+ | No log | 7.1692 | 466 | 1.0782 | 0.4803 | 1.0782 | 1.0384 |
285
+ | No log | 7.2 | 468 | 1.0332 | 0.4400 | 1.0332 | 1.0165 |
286
+ | No log | 7.2308 | 470 | 0.9719 | 0.4540 | 0.9719 | 0.9859 |
287
+ | No log | 7.2615 | 472 | 0.9470 | 0.5014 | 0.9470 | 0.9731 |
288
+ | No log | 7.2923 | 474 | 0.9043 | 0.4568 | 0.9043 | 0.9509 |
289
+ | No log | 7.3231 | 476 | 0.8581 | 0.5270 | 0.8581 | 0.9263 |
290
+ | No log | 7.3538 | 478 | 0.7974 | 0.5580 | 0.7974 | 0.8930 |
291
+ | No log | 7.3846 | 480 | 0.7834 | 0.4929 | 0.7834 | 0.8851 |
292
+ | No log | 7.4154 | 482 | 0.7807 | 0.5540 | 0.7807 | 0.8836 |
293
+ | No log | 7.4462 | 484 | 0.7842 | 0.5987 | 0.7842 | 0.8855 |
294
+ | No log | 7.4769 | 486 | 0.8219 | 0.5013 | 0.8219 | 0.9066 |
295
+ | No log | 7.5077 | 488 | 0.8099 | 0.5352 | 0.8099 | 0.9000 |
296
+ | No log | 7.5385 | 490 | 0.7788 | 0.5676 | 0.7788 | 0.8825 |
297
+ | No log | 7.5692 | 492 | 0.7946 | 0.5025 | 0.7946 | 0.8914 |
298
+ | No log | 7.6 | 494 | 0.8963 | 0.4285 | 0.8963 | 0.9467 |
299
+ | No log | 7.6308 | 496 | 0.9033 | 0.4630 | 0.9033 | 0.9504 |
300
+ | No log | 7.6615 | 498 | 0.8422 | 0.4763 | 0.8422 | 0.9177 |
301
+ | 0.3877 | 7.6923 | 500 | 0.7984 | 0.5870 | 0.7984 | 0.8935 |
302
+ | 0.3877 | 7.7231 | 502 | 0.8048 | 0.5196 | 0.8048 | 0.8971 |
303
+ | 0.3877 | 7.7538 | 504 | 0.8338 | 0.5720 | 0.8338 | 0.9131 |
304
+ | 0.3877 | 7.7846 | 506 | 0.8540 | 0.5579 | 0.8540 | 0.9241 |
305
+ | 0.3877 | 7.8154 | 508 | 0.8129 | 0.5596 | 0.8129 | 0.9016 |
306
+ | 0.3877 | 7.8462 | 510 | 0.7869 | 0.5726 | 0.7869 | 0.8871 |
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:a1567da63be1e63af341bbc8de8208fd15ae9e4335114b8256e0e9d886ab05a8
3
+ size 540799996
training_args.bin ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:8640323bab7b5f66fbb06cf9bdcf407418390af50c7afaa788f5587ed9ec37ab
3
+ size 5368