Hugging Face's logo

MayBashendy
/
ArabicNewSplits8_usingALLEssays_FineTuningAraBERT_run3_AugV5_k9_task2_organization

Text Classification
Transformers
Safetensors
bert
Generated from Trainer
Inference Endpoints
Model card Files Community
MayBashendy commited on
Commit
870ff6f
·
verified ·
1 Parent(s): 7c73584

Training in progress, step 500

Browse files
Files changed (4) hide show
  1. README.md +362 -0
  2. config.json +32 -0
  3. model.safetensors +3 -0
  4. training_args.bin +3 -0
README.md ADDED
@@ -0,0 +1,362 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ library_name: transformers
3
+ base_model: aubmindlab/bert-base-arabertv02
4
+ tags:
5
+ - generated_from_trainer
6
+ model-index:
7
+ - name: ArabicNewSplits8_usingALLEssays_FineTuningAraBERT_run3_AugV5_k8_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
+ # ArabicNewSplits8_usingALLEssays_FineTuningAraBERT_run3_AugV5_k8_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: 0.5691
19
+ - Qwk: 0.4368
20
+ - Mse: 0.5691
21
+ - Rmse: 0.7544
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 | 0.0476 | 2 | 4.4110 | -0.0315 | 4.4110 | 2.1002 |
53
+ | No log | 0.0952 | 4 | 2.7729 | -0.0339 | 2.7729 | 1.6652 |
54
+ | No log | 0.1429 | 6 | 3.0646 | -0.1292 | 3.0646 | 1.7506 |
55
+ | No log | 0.1905 | 8 | 2.4227 | -0.1660 | 2.4227 | 1.5565 |
56
+ | No log | 0.2381 | 10 | 1.1109 | -0.0016 | 1.1109 | 1.0540 |
57
+ | No log | 0.2857 | 12 | 0.9411 | 0.1196 | 0.9411 | 0.9701 |
58
+ | No log | 0.3333 | 14 | 1.9100 | -0.0262 | 1.9100 | 1.3820 |
59
+ | No log | 0.3810 | 16 | 1.7786 | -0.0139 | 1.7786 | 1.3336 |
60
+ | No log | 0.4286 | 18 | 1.0136 | 0.1363 | 1.0136 | 1.0068 |
61
+ | No log | 0.4762 | 20 | 0.8147 | 0.1844 | 0.8147 | 0.9026 |
62
+ | No log | 0.5238 | 22 | 0.8085 | 0.1058 | 0.8085 | 0.8992 |
63
+ | No log | 0.5714 | 24 | 0.7938 | 0.0516 | 0.7938 | 0.8910 |
64
+ | No log | 0.6190 | 26 | 0.7743 | 0.1481 | 0.7743 | 0.8799 |
65
+ | No log | 0.6667 | 28 | 0.7352 | 0.2979 | 0.7352 | 0.8574 |
66
+ | No log | 0.7143 | 30 | 0.7992 | 0.2109 | 0.7992 | 0.8940 |
67
+ | No log | 0.7619 | 32 | 0.7787 | 0.2751 | 0.7787 | 0.8824 |
68
+ | No log | 0.8095 | 34 | 0.6847 | 0.3874 | 0.6847 | 0.8275 |
69
+ | No log | 0.8571 | 36 | 0.6881 | 0.4241 | 0.6881 | 0.8295 |
70
+ | No log | 0.9048 | 38 | 0.8796 | 0.3289 | 0.8796 | 0.9379 |
71
+ | No log | 0.9524 | 40 | 1.4598 | 0.2257 | 1.4598 | 1.2082 |
72
+ | No log | 1.0 | 42 | 1.7806 | 0.1536 | 1.7806 | 1.3344 |
73
+ | No log | 1.0476 | 44 | 1.7099 | 0.1636 | 1.7099 | 1.3076 |
74
+ | No log | 1.0952 | 46 | 1.3750 | 0.2000 | 1.3750 | 1.1726 |
75
+ | No log | 1.1429 | 48 | 0.8878 | 0.3972 | 0.8878 | 0.9422 |
76
+ | No log | 1.1905 | 50 | 0.6731 | 0.4633 | 0.6731 | 0.8204 |
77
+ | No log | 1.2381 | 52 | 0.6397 | 0.4580 | 0.6397 | 0.7998 |
78
+ | No log | 1.2857 | 54 | 0.6173 | 0.3843 | 0.6173 | 0.7857 |
79
+ | No log | 1.3333 | 56 | 0.6143 | 0.4830 | 0.6143 | 0.7838 |
80
+ | No log | 1.3810 | 58 | 0.6994 | 0.3708 | 0.6994 | 0.8363 |
81
+ | No log | 1.4286 | 60 | 0.7905 | 0.2947 | 0.7905 | 0.8891 |
82
+ | No log | 1.4762 | 62 | 0.7185 | 0.3815 | 0.7185 | 0.8476 |
83
+ | No log | 1.5238 | 64 | 0.7025 | 0.3668 | 0.7025 | 0.8382 |
84
+ | No log | 1.5714 | 66 | 0.8251 | 0.3588 | 0.8251 | 0.9083 |
85
+ | No log | 1.6190 | 68 | 0.9942 | 0.3359 | 0.9942 | 0.9971 |
86
+ | No log | 1.6667 | 70 | 0.9806 | 0.3589 | 0.9806 | 0.9902 |
87
+ | No log | 1.7143 | 72 | 0.8719 | 0.4230 | 0.8719 | 0.9337 |
88
+ | No log | 1.7619 | 74 | 0.8163 | 0.5045 | 0.8163 | 0.9035 |
89
+ | No log | 1.8095 | 76 | 0.8229 | 0.4796 | 0.8229 | 0.9071 |
90
+ | No log | 1.8571 | 78 | 0.8342 | 0.4561 | 0.8342 | 0.9133 |
91
+ | No log | 1.9048 | 80 | 0.6901 | 0.5048 | 0.6901 | 0.8307 |
92
+ | No log | 1.9524 | 82 | 0.6153 | 0.5671 | 0.6153 | 0.7844 |
93
+ | No log | 2.0 | 84 | 0.6721 | 0.4417 | 0.6721 | 0.8198 |
94
+ | No log | 2.0476 | 86 | 0.7187 | 0.4287 | 0.7187 | 0.8478 |
95
+ | No log | 2.0952 | 88 | 0.6973 | 0.5634 | 0.6973 | 0.8350 |
96
+ | No log | 2.1429 | 90 | 0.7681 | 0.4925 | 0.7681 | 0.8764 |
97
+ | No log | 2.1905 | 92 | 0.9891 | 0.4079 | 0.9891 | 0.9945 |
98
+ | No log | 2.2381 | 94 | 1.0057 | 0.4104 | 1.0057 | 1.0028 |
99
+ | No log | 2.2857 | 96 | 0.8528 | 0.4719 | 0.8528 | 0.9235 |
100
+ | No log | 2.3333 | 98 | 0.7600 | 0.5655 | 0.7600 | 0.8718 |
101
+ | No log | 2.3810 | 100 | 0.6747 | 0.5596 | 0.6747 | 0.8214 |
102
+ | No log | 2.4286 | 102 | 0.6728 | 0.5034 | 0.6728 | 0.8202 |
103
+ | No log | 2.4762 | 104 | 0.6992 | 0.5748 | 0.6992 | 0.8362 |
104
+ | No log | 2.5238 | 106 | 0.9037 | 0.4206 | 0.9037 | 0.9506 |
105
+ | No log | 2.5714 | 108 | 0.9558 | 0.3944 | 0.9558 | 0.9776 |
106
+ | No log | 2.6190 | 110 | 0.8604 | 0.4449 | 0.8604 | 0.9276 |
107
+ | No log | 2.6667 | 112 | 0.8482 | 0.4536 | 0.8482 | 0.9210 |
108
+ | No log | 2.7143 | 114 | 0.8869 | 0.4449 | 0.8869 | 0.9418 |
109
+ | No log | 2.7619 | 116 | 0.7814 | 0.4861 | 0.7814 | 0.8840 |
110
+ | No log | 2.8095 | 118 | 0.6860 | 0.5565 | 0.6860 | 0.8283 |
111
+ | No log | 2.8571 | 120 | 0.6634 | 0.4968 | 0.6634 | 0.8145 |
112
+ | No log | 2.9048 | 122 | 0.7012 | 0.5426 | 0.7012 | 0.8374 |
113
+ | No log | 2.9524 | 124 | 0.7346 | 0.5525 | 0.7346 | 0.8571 |
114
+ | No log | 3.0 | 126 | 0.7372 | 0.5501 | 0.7372 | 0.8586 |
115
+ | No log | 3.0476 | 128 | 0.8362 | 0.5038 | 0.8362 | 0.9145 |
116
+ | No log | 3.0952 | 130 | 0.9898 | 0.3876 | 0.9898 | 0.9949 |
117
+ | No log | 3.1429 | 132 | 0.8730 | 0.4965 | 0.8730 | 0.9343 |
118
+ | No log | 3.1905 | 134 | 0.7123 | 0.5392 | 0.7123 | 0.8440 |
119
+ | No log | 3.2381 | 136 | 0.6788 | 0.5327 | 0.6788 | 0.8239 |
120
+ | No log | 3.2857 | 138 | 0.6856 | 0.5287 | 0.6856 | 0.8280 |
121
+ | No log | 3.3333 | 140 | 0.7216 | 0.5447 | 0.7216 | 0.8495 |
122
+ | No log | 3.3810 | 142 | 0.8615 | 0.4556 | 0.8615 | 0.9282 |
123
+ | No log | 3.4286 | 144 | 0.9581 | 0.3627 | 0.9581 | 0.9788 |
124
+ | No log | 3.4762 | 146 | 0.9120 | 0.4539 | 0.9120 | 0.9550 |
125
+ | No log | 3.5238 | 148 | 0.8047 | 0.5434 | 0.8047 | 0.8971 |
126
+ | No log | 3.5714 | 150 | 0.7919 | 0.5647 | 0.7919 | 0.8899 |
127
+ | No log | 3.6190 | 152 | 0.7872 | 0.5647 | 0.7872 | 0.8872 |
128
+ | No log | 3.6667 | 154 | 0.7719 | 0.5580 | 0.7719 | 0.8786 |
129
+ | No log | 3.7143 | 156 | 0.8896 | 0.4615 | 0.8896 | 0.9432 |
130
+ | No log | 3.7619 | 158 | 0.9534 | 0.3902 | 0.9534 | 0.9764 |
131
+ | No log | 3.8095 | 160 | 0.8634 | 0.4760 | 0.8634 | 0.9292 |
132
+ | No log | 3.8571 | 162 | 0.8254 | 0.4675 | 0.8254 | 0.9085 |
133
+ | No log | 3.9048 | 164 | 0.8056 | 0.4659 | 0.8056 | 0.8975 |
134
+ | No log | 3.9524 | 166 | 0.7602 | 0.5055 | 0.7602 | 0.8719 |
135
+ | No log | 4.0 | 168 | 0.6733 | 0.5709 | 0.6733 | 0.8206 |
136
+ | No log | 4.0476 | 170 | 0.6417 | 0.5141 | 0.6417 | 0.8011 |
137
+ | No log | 4.0952 | 172 | 0.6451 | 0.5291 | 0.6451 | 0.8032 |
138
+ | No log | 4.1429 | 174 | 0.7263 | 0.5307 | 0.7263 | 0.8522 |
139
+ | No log | 4.1905 | 176 | 0.7048 | 0.5324 | 0.7048 | 0.8395 |
140
+ | No log | 4.2381 | 178 | 0.6957 | 0.5682 | 0.6957 | 0.8341 |
141
+ | No log | 4.2857 | 180 | 0.6717 | 0.4946 | 0.6717 | 0.8196 |
142
+ | No log | 4.3333 | 182 | 0.7068 | 0.4927 | 0.7068 | 0.8407 |
143
+ | No log | 4.3810 | 184 | 0.7268 | 0.5027 | 0.7268 | 0.8525 |
144
+ | No log | 4.4286 | 186 | 0.7161 | 0.5021 | 0.7161 | 0.8462 |
145
+ | No log | 4.4762 | 188 | 0.7441 | 0.4535 | 0.7441 | 0.8626 |
146
+ | No log | 4.5238 | 190 | 0.7175 | 0.4496 | 0.7175 | 0.8470 |
147
+ | No log | 4.5714 | 192 | 0.6791 | 0.4671 | 0.6791 | 0.8241 |
148
+ | No log | 4.6190 | 194 | 0.7338 | 0.48 | 0.7338 | 0.8566 |
149
+ | No log | 4.6667 | 196 | 0.9203 | 0.3898 | 0.9203 | 0.9593 |
150
+ | No log | 4.7143 | 198 | 0.9761 | 0.3844 | 0.9761 | 0.9880 |
151
+ | No log | 4.7619 | 200 | 0.8031 | 0.4735 | 0.8031 | 0.8962 |
152
+ | No log | 4.8095 | 202 | 0.6451 | 0.4173 | 0.6451 | 0.8032 |
153
+ | No log | 4.8571 | 204 | 0.6182 | 0.4057 | 0.6182 | 0.7863 |
154
+ | No log | 4.9048 | 206 | 0.6396 | 0.4371 | 0.6396 | 0.7998 |
155
+ | No log | 4.9524 | 208 | 0.6271 | 0.4882 | 0.6271 | 0.7919 |
156
+ | No log | 5.0 | 210 | 0.6490 | 0.4967 | 0.6490 | 0.8056 |
157
+ | No log | 5.0476 | 212 | 0.6752 | 0.5176 | 0.6752 | 0.8217 |
158
+ | No log | 5.0952 | 214 | 0.7118 | 0.5337 | 0.7118 | 0.8437 |
159
+ | No log | 5.1429 | 216 | 0.7129 | 0.5264 | 0.7129 | 0.8443 |
160
+ | No log | 5.1905 | 218 | 0.6931 | 0.5505 | 0.6931 | 0.8325 |
161
+ | No log | 5.2381 | 220 | 0.6894 | 0.5029 | 0.6894 | 0.8303 |
162
+ | No log | 5.2857 | 222 | 0.6577 | 0.4904 | 0.6577 | 0.8110 |
163
+ | No log | 5.3333 | 224 | 0.6165 | 0.4763 | 0.6165 | 0.7852 |
164
+ | No log | 5.3810 | 226 | 0.6798 | 0.5009 | 0.6798 | 0.8245 |
165
+ | No log | 5.4286 | 228 | 0.7446 | 0.4799 | 0.7446 | 0.8629 |
166
+ | No log | 5.4762 | 230 | 0.7287 | 0.5294 | 0.7287 | 0.8536 |
167
+ | No log | 5.5238 | 232 | 0.6714 | 0.5484 | 0.6714 | 0.8194 |
168
+ | No log | 5.5714 | 234 | 0.6874 | 0.5081 | 0.6874 | 0.8291 |
169
+ | No log | 5.6190 | 236 | 0.6983 | 0.4976 | 0.6983 | 0.8357 |
170
+ | No log | 5.6667 | 238 | 0.7152 | 0.5409 | 0.7152 | 0.8457 |
171
+ | No log | 5.7143 | 240 | 0.7180 | 0.5365 | 0.7180 | 0.8473 |
172
+ | No log | 5.7619 | 242 | 0.6763 | 0.5029 | 0.6763 | 0.8223 |
173
+ | No log | 5.8095 | 244 | 0.6612 | 0.4627 | 0.6612 | 0.8132 |
174
+ | No log | 5.8571 | 246 | 0.6596 | 0.4787 | 0.6596 | 0.8122 |
175
+ | No log | 5.9048 | 248 | 0.6611 | 0.4708 | 0.6611 | 0.8131 |
176
+ | No log | 5.9524 | 250 | 0.6585 | 0.4373 | 0.6585 | 0.8115 |
177
+ | No log | 6.0 | 252 | 0.6778 | 0.4542 | 0.6778 | 0.8233 |
178
+ | No log | 6.0476 | 254 | 0.7054 | 0.4915 | 0.7054 | 0.8399 |
179
+ | No log | 6.0952 | 256 | 0.7219 | 0.4899 | 0.7219 | 0.8497 |
180
+ | No log | 6.1429 | 258 | 0.7749 | 0.5507 | 0.7749 | 0.8803 |
181
+ | No log | 6.1905 | 260 | 0.8156 | 0.5257 | 0.8156 | 0.9031 |
182
+ | No log | 6.2381 | 262 | 0.7928 | 0.5050 | 0.7928 | 0.8904 |
183
+ | No log | 6.2857 | 264 | 0.8015 | 0.5268 | 0.8015 | 0.8953 |
184
+ | No log | 6.3333 | 266 | 0.7113 | 0.5334 | 0.7113 | 0.8434 |
185
+ | No log | 6.3810 | 268 | 0.7308 | 0.4815 | 0.7308 | 0.8549 |
186
+ | No log | 6.4286 | 270 | 0.7995 | 0.4567 | 0.7995 | 0.8942 |
187
+ | No log | 6.4762 | 272 | 0.8030 | 0.4337 | 0.8030 | 0.8961 |
188
+ | No log | 6.5238 | 274 | 0.7575 | 0.4288 | 0.7575 | 0.8704 |
189
+ | No log | 6.5714 | 276 | 0.7263 | 0.4301 | 0.7263 | 0.8522 |
190
+ | No log | 6.6190 | 278 | 0.7189 | 0.4336 | 0.7189 | 0.8479 |
191
+ | No log | 6.6667 | 280 | 0.6943 | 0.4386 | 0.6943 | 0.8333 |
192
+ | No log | 6.7143 | 282 | 0.6800 | 0.4834 | 0.6800 | 0.8246 |
193
+ | No log | 6.7619 | 284 | 0.6627 | 0.4808 | 0.6627 | 0.8141 |
194
+ | No log | 6.8095 | 286 | 0.6325 | 0.4498 | 0.6325 | 0.7953 |
195
+ | No log | 6.8571 | 288 | 0.6210 | 0.5264 | 0.6210 | 0.7880 |
196
+ | No log | 6.9048 | 290 | 0.6637 | 0.5714 | 0.6637 | 0.8147 |
197
+ | No log | 6.9524 | 292 | 0.7879 | 0.5013 | 0.7879 | 0.8877 |
198
+ | No log | 7.0 | 294 | 0.8184 | 0.4582 | 0.8184 | 0.9047 |
199
+ | No log | 7.0476 | 296 | 0.8020 | 0.4793 | 0.8020 | 0.8956 |
200
+ | No log | 7.0952 | 298 | 0.7170 | 0.5902 | 0.7170 | 0.8467 |
201
+ | No log | 7.1429 | 300 | 0.6457 | 0.5449 | 0.6457 | 0.8036 |
202
+ | No log | 7.1905 | 302 | 0.6488 | 0.5078 | 0.6488 | 0.8055 |
203
+ | No log | 7.2381 | 304 | 0.6383 | 0.5316 | 0.6383 | 0.7989 |
204
+ | No log | 7.2857 | 306 | 0.6550 | 0.5327 | 0.6550 | 0.8093 |
205
+ | No log | 7.3333 | 308 | 0.6852 | 0.5161 | 0.6852 | 0.8278 |
206
+ | No log | 7.3810 | 310 | 0.6490 | 0.4712 | 0.6490 | 0.8056 |
207
+ | No log | 7.4286 | 312 | 0.6305 | 0.4857 | 0.6305 | 0.7941 |
208
+ | No log | 7.4762 | 314 | 0.6060 | 0.5228 | 0.6060 | 0.7785 |
209
+ | No log | 7.5238 | 316 | 0.6344 | 0.4588 | 0.6344 | 0.7965 |
210
+ | No log | 7.5714 | 318 | 0.6620 | 0.4433 | 0.6620 | 0.8136 |
211
+ | No log | 7.6190 | 320 | 0.6436 | 0.4513 | 0.6436 | 0.8023 |
212
+ | No log | 7.6667 | 322 | 0.6191 | 0.5290 | 0.6191 | 0.7869 |
213
+ | No log | 7.7143 | 324 | 0.6118 | 0.5083 | 0.6118 | 0.7821 |
214
+ | No log | 7.7619 | 326 | 0.6637 | 0.5348 | 0.6637 | 0.8147 |
215
+ | No log | 7.8095 | 328 | 0.6986 | 0.5247 | 0.6986 | 0.8358 |
216
+ | No log | 7.8571 | 330 | 0.6663 | 0.5199 | 0.6663 | 0.8163 |
217
+ | No log | 7.9048 | 332 | 0.6403 | 0.4914 | 0.6403 | 0.8002 |
218
+ | No log | 7.9524 | 334 | 0.6472 | 0.4659 | 0.6472 | 0.8045 |
219
+ | No log | 8.0 | 336 | 0.6499 | 0.4714 | 0.6499 | 0.8061 |
220
+ | No log | 8.0476 | 338 | 0.6670 | 0.5248 | 0.6670 | 0.8167 |
221
+ | No log | 8.0952 | 340 | 0.6754 | 0.4978 | 0.6754 | 0.8218 |
222
+ | No log | 8.1429 | 342 | 0.6458 | 0.5191 | 0.6458 | 0.8036 |
223
+ | No log | 8.1905 | 344 | 0.6427 | 0.4667 | 0.6427 | 0.8017 |
224
+ | No log | 8.2381 | 346 | 0.6495 | 0.4711 | 0.6495 | 0.8059 |
225
+ | No log | 8.2857 | 348 | 0.6122 | 0.4321 | 0.6122 | 0.7825 |
226
+ | No log | 8.3333 | 350 | 0.5956 | 0.4763 | 0.5956 | 0.7717 |
227
+ | No log | 8.3810 | 352 | 0.6444 | 0.4599 | 0.6444 | 0.8028 |
228
+ | No log | 8.4286 | 354 | 0.6947 | 0.4990 | 0.6947 | 0.8335 |
229
+ | No log | 8.4762 | 356 | 0.6912 | 0.5114 | 0.6912 | 0.8314 |
230
+ | No log | 8.5238 | 358 | 0.6920 | 0.5236 | 0.6920 | 0.8319 |
231
+ | No log | 8.5714 | 360 | 0.6974 | 0.5515 | 0.6974 | 0.8351 |
232
+ | No log | 8.6190 | 362 | 0.6826 | 0.5140 | 0.6826 | 0.8262 |
233
+ | No log | 8.6667 | 364 | 0.6482 | 0.5079 | 0.6482 | 0.8051 |
234
+ | No log | 8.7143 | 366 | 0.6220 | 0.5095 | 0.6220 | 0.7887 |
235
+ | No log | 8.7619 | 368 | 0.6193 | 0.4811 | 0.6193 | 0.7869 |
236
+ | No log | 8.8095 | 370 | 0.6334 | 0.4691 | 0.6334 | 0.7958 |
237
+ | No log | 8.8571 | 372 | 0.6180 | 0.4654 | 0.6180 | 0.7862 |
238
+ | No log | 8.9048 | 374 | 0.6123 | 0.4277 | 0.6123 | 0.7825 |
239
+ | No log | 8.9524 | 376 | 0.6085 | 0.4377 | 0.6085 | 0.7800 |
240
+ | No log | 9.0 | 378 | 0.6595 | 0.4164 | 0.6595 | 0.8121 |
241
+ | No log | 9.0476 | 380 | 0.7242 | 0.4704 | 0.7242 | 0.8510 |
242
+ | No log | 9.0952 | 382 | 0.7213 | 0.4704 | 0.7213 | 0.8493 |
243
+ | No log | 9.1429 | 384 | 0.6340 | 0.4630 | 0.6340 | 0.7962 |
244
+ | No log | 9.1905 | 386 | 0.6274 | 0.5259 | 0.6274 | 0.7921 |
245
+ | No log | 9.2381 | 388 | 0.6537 | 0.5392 | 0.6537 | 0.8085 |
246
+ | No log | 9.2857 | 390 | 0.6655 | 0.5473 | 0.6655 | 0.8158 |
247
+ | No log | 9.3333 | 392 | 0.6719 | 0.5473 | 0.6719 | 0.8197 |
248
+ | No log | 9.3810 | 394 | 0.6549 | 0.5129 | 0.6549 | 0.8093 |
249
+ | No log | 9.4286 | 396 | 0.6733 | 0.5288 | 0.6733 | 0.8206 |
250
+ | No log | 9.4762 | 398 | 0.6678 | 0.4824 | 0.6678 | 0.8172 |
251
+ | No log | 9.5238 | 400 | 0.6175 | 0.4092 | 0.6175 | 0.7858 |
252
+ | No log | 9.5714 | 402 | 0.5990 | 0.4025 | 0.5990 | 0.7739 |
253
+ | No log | 9.6190 | 404 | 0.5990 | 0.3920 | 0.5990 | 0.7740 |
254
+ | No log | 9.6667 | 406 | 0.6163 | 0.4648 | 0.6163 | 0.7850 |
255
+ | No log | 9.7143 | 408 | 0.6386 | 0.4437 | 0.6386 | 0.7991 |
256
+ | No log | 9.7619 | 410 | 0.6561 | 0.4430 | 0.6561 | 0.8100 |
257
+ | No log | 9.8095 | 412 | 0.6543 | 0.4449 | 0.6543 | 0.8089 |
258
+ | No log | 9.8571 | 414 | 0.6608 | 0.4358 | 0.6608 | 0.8129 |
259
+ | No log | 9.9048 | 416 | 0.6437 | 0.4309 | 0.6437 | 0.8023 |
260
+ | No log | 9.9524 | 418 | 0.6111 | 0.4315 | 0.6111 | 0.7818 |
261
+ | No log | 10.0 | 420 | 0.6399 | 0.4367 | 0.6399 | 0.7999 |
262
+ | No log | 10.0476 | 422 | 0.6892 | 0.4649 | 0.6892 | 0.8302 |
263
+ | No log | 10.0952 | 424 | 0.6832 | 0.4649 | 0.6832 | 0.8266 |
264
+ | No log | 10.1429 | 426 | 0.6212 | 0.4379 | 0.6212 | 0.7881 |
265
+ | No log | 10.1905 | 428 | 0.6103 | 0.4326 | 0.6103 | 0.7812 |
266
+ | No log | 10.2381 | 430 | 0.5943 | 0.4536 | 0.5943 | 0.7709 |
267
+ | No log | 10.2857 | 432 | 0.5915 | 0.4619 | 0.5915 | 0.7691 |
268
+ | No log | 10.3333 | 434 | 0.6149 | 0.5044 | 0.6149 | 0.7841 |
269
+ | No log | 10.3810 | 436 | 0.6158 | 0.4614 | 0.6158 | 0.7847 |
270
+ | No log | 10.4286 | 438 | 0.6485 | 0.4838 | 0.6485 | 0.8053 |
271
+ | No log | 10.4762 | 440 | 0.7008 | 0.5305 | 0.7008 | 0.8371 |
272
+ | No log | 10.5238 | 442 | 0.6752 | 0.4886 | 0.6752 | 0.8217 |
273
+ | No log | 10.5714 | 444 | 0.6533 | 0.4980 | 0.6533 | 0.8083 |
274
+ | No log | 10.6190 | 446 | 0.6497 | 0.4932 | 0.6497 | 0.8060 |
275
+ | No log | 10.6667 | 448 | 0.6484 | 0.5271 | 0.6484 | 0.8052 |
276
+ | No log | 10.7143 | 450 | 0.6516 | 0.4829 | 0.6516 | 0.8072 |
277
+ | No log | 10.7619 | 452 | 0.6399 | 0.5274 | 0.6399 | 0.7999 |
278
+ | No log | 10.8095 | 454 | 0.6209 | 0.4798 | 0.6209 | 0.7880 |
279
+ | No log | 10.8571 | 456 | 0.6117 | 0.4805 | 0.6117 | 0.7821 |
280
+ | No log | 10.9048 | 458 | 0.6121 | 0.4891 | 0.6121 | 0.7824 |
281
+ | No log | 10.9524 | 460 | 0.6189 | 0.4755 | 0.6189 | 0.7867 |
282
+ | No log | 11.0 | 462 | 0.5965 | 0.4465 | 0.5965 | 0.7724 |
283
+ | No log | 11.0476 | 464 | 0.5837 | 0.4355 | 0.5837 | 0.7640 |
284
+ | No log | 11.0952 | 466 | 0.5811 | 0.4322 | 0.5811 | 0.7623 |
285
+ | No log | 11.1429 | 468 | 0.5785 | 0.4332 | 0.5785 | 0.7606 |
286
+ | No log | 11.1905 | 470 | 0.5852 | 0.4388 | 0.5852 | 0.7650 |
287
+ | No log | 11.2381 | 472 | 0.6064 | 0.4535 | 0.6064 | 0.7787 |
288
+ | No log | 11.2857 | 474 | 0.6242 | 0.4932 | 0.6242 | 0.7901 |
289
+ | No log | 11.3333 | 476 | 0.6406 | 0.4684 | 0.6406 | 0.8004 |
290
+ | No log | 11.3810 | 478 | 0.6521 | 0.5035 | 0.6521 | 0.8075 |
291
+ | No log | 11.4286 | 480 | 0.6285 | 0.4827 | 0.6285 | 0.7927 |
292
+ | No log | 11.4762 | 482 | 0.6067 | 0.4467 | 0.6067 | 0.7789 |
293
+ | No log | 11.5238 | 484 | 0.5998 | 0.4352 | 0.5998 | 0.7744 |
294
+ | No log | 11.5714 | 486 | 0.6080 | 0.4648 | 0.6080 | 0.7797 |
295
+ | No log | 11.6190 | 488 | 0.6182 | 0.5044 | 0.6182 | 0.7863 |
296
+ | No log | 11.6667 | 490 | 0.6225 | 0.5219 | 0.6225 | 0.7890 |
297
+ | No log | 11.7143 | 492 | 0.6150 | 0.4999 | 0.6150 | 0.7842 |
298
+ | No log | 11.7619 | 494 | 0.6165 | 0.5171 | 0.6165 | 0.7852 |
299
+ | No log | 11.8095 | 496 | 0.6359 | 0.4797 | 0.6359 | 0.7975 |
300
+ | No log | 11.8571 | 498 | 0.6528 | 0.5096 | 0.6528 | 0.8079 |
301
+ | 0.3541 | 11.9048 | 500 | 0.6462 | 0.4952 | 0.6462 | 0.8038 |
302
+ | 0.3541 | 11.9524 | 502 | 0.6317 | 0.5251 | 0.6317 | 0.7948 |
303
+ | 0.3541 | 12.0 | 504 | 0.6315 | 0.5306 | 0.6315 | 0.7946 |
304
+ | 0.3541 | 12.0476 | 506 | 0.6491 | 0.5060 | 0.6491 | 0.8057 |
305
+ | 0.3541 | 12.0952 | 508 | 0.7027 | 0.5260 | 0.7027 | 0.8383 |
306
+ | 0.3541 | 12.1429 | 510 | 0.7254 | 0.4822 | 0.7254 | 0.8517 |
307
+ | 0.3541 | 12.1905 | 512 | 0.7062 | 0.5198 | 0.7062 | 0.8403 |
308
+ | 0.3541 | 12.2381 | 514 | 0.6362 | 0.5450 | 0.6362 | 0.7976 |
309
+ | 0.3541 | 12.2857 | 516 | 0.5988 | 0.5588 | 0.5988 | 0.7738 |
310
+ | 0.3541 | 12.3333 | 518 | 0.6215 | 0.5321 | 0.6215 | 0.7884 |
311
+ | 0.3541 | 12.3810 | 520 | 0.6836 | 0.4913 | 0.6836 | 0.8268 |
312
+ | 0.3541 | 12.4286 | 522 | 0.6731 | 0.5074 | 0.6731 | 0.8204 |
313
+ | 0.3541 | 12.4762 | 524 | 0.6611 | 0.5286 | 0.6611 | 0.8131 |
314
+ | 0.3541 | 12.5238 | 526 | 0.5888 | 0.5613 | 0.5888 | 0.7673 |
315
+ | 0.3541 | 12.5714 | 528 | 0.5626 | 0.5177 | 0.5626 | 0.7501 |
316
+ | 0.3541 | 12.6190 | 530 | 0.5474 | 0.5193 | 0.5474 | 0.7398 |
317
+ | 0.3541 | 12.6667 | 532 | 0.5588 | 0.5219 | 0.5588 | 0.7475 |
318
+ | 0.3541 | 12.7143 | 534 | 0.5849 | 0.5641 | 0.5849 | 0.7648 |
319
+ | 0.3541 | 12.7619 | 536 | 0.6104 | 0.5344 | 0.6104 | 0.7813 |
320
+ | 0.3541 | 12.8095 | 538 | 0.6462 | 0.5176 | 0.6462 | 0.8039 |
321
+ | 0.3541 | 12.8571 | 540 | 0.6140 | 0.5153 | 0.6140 | 0.7836 |
322
+ | 0.3541 | 12.9048 | 542 | 0.5762 | 0.5397 | 0.5762 | 0.7591 |
323
+ | 0.3541 | 12.9524 | 544 | 0.6247 | 0.5449 | 0.6247 | 0.7904 |
324
+ | 0.3541 | 13.0 | 546 | 0.6899 | 0.4751 | 0.6899 | 0.8306 |
325
+ | 0.3541 | 13.0476 | 548 | 0.6733 | 0.4996 | 0.6733 | 0.8205 |
326
+ | 0.3541 | 13.0952 | 550 | 0.6166 | 0.5218 | 0.6166 | 0.7852 |
327
+ | 0.3541 | 13.1429 | 552 | 0.6457 | 0.5193 | 0.6457 | 0.8036 |
328
+ | 0.3541 | 13.1905 | 554 | 0.6854 | 0.4915 | 0.6854 | 0.8279 |
329
+ | 0.3541 | 13.2381 | 556 | 0.6578 | 0.5151 | 0.6578 | 0.8110 |
330
+ | 0.3541 | 13.2857 | 558 | 0.6328 | 0.5330 | 0.6328 | 0.7955 |
331
+ | 0.3541 | 13.3333 | 560 | 0.6088 | 0.5075 | 0.6088 | 0.7803 |
332
+ | 0.3541 | 13.3810 | 562 | 0.6171 | 0.5301 | 0.6171 | 0.7856 |
333
+ | 0.3541 | 13.4286 | 564 | 0.5989 | 0.4956 | 0.5989 | 0.7739 |
334
+ | 0.3541 | 13.4762 | 566 | 0.6183 | 0.4721 | 0.6183 | 0.7863 |
335
+ | 0.3541 | 13.5238 | 568 | 0.6309 | 0.4235 | 0.6309 | 0.7943 |
336
+ | 0.3541 | 13.5714 | 570 | 0.6026 | 0.4598 | 0.6026 | 0.7763 |
337
+ | 0.3541 | 13.6190 | 572 | 0.5861 | 0.5051 | 0.5861 | 0.7656 |
338
+ | 0.3541 | 13.6667 | 574 | 0.5880 | 0.5018 | 0.5880 | 0.7668 |
339
+ | 0.3541 | 13.7143 | 576 | 0.6023 | 0.5773 | 0.6023 | 0.7761 |
340
+ | 0.3541 | 13.7619 | 578 | 0.6053 | 0.5228 | 0.6053 | 0.7780 |
341
+ | 0.3541 | 13.8095 | 580 | 0.6431 | 0.5363 | 0.6431 | 0.8020 |
342
+ | 0.3541 | 13.8571 | 582 | 0.6448 | 0.4931 | 0.6448 | 0.8030 |
343
+ | 0.3541 | 13.9048 | 584 | 0.6269 | 0.5184 | 0.6269 | 0.7918 |
344
+ | 0.3541 | 13.9524 | 586 | 0.6082 | 0.5103 | 0.6082 | 0.7799 |
345
+ | 0.3541 | 14.0 | 588 | 0.6500 | 0.4939 | 0.6500 | 0.8062 |
346
+ | 0.3541 | 14.0476 | 590 | 0.6818 | 0.4825 | 0.6818 | 0.8257 |
347
+ | 0.3541 | 14.0952 | 592 | 0.6633 | 0.4941 | 0.6633 | 0.8145 |
348
+ | 0.3541 | 14.1429 | 594 | 0.6280 | 0.5347 | 0.6280 | 0.7925 |
349
+ | 0.3541 | 14.1905 | 596 | 0.6173 | 0.5048 | 0.6173 | 0.7857 |
350
+ | 0.3541 | 14.2381 | 598 | 0.6117 | 0.4744 | 0.6117 | 0.7821 |
351
+ | 0.3541 | 14.2857 | 600 | 0.5854 | 0.4241 | 0.5854 | 0.7651 |
352
+ | 0.3541 | 14.3333 | 602 | 0.5693 | 0.4562 | 0.5693 | 0.7546 |
353
+ | 0.3541 | 14.3810 | 604 | 0.5661 | 0.4725 | 0.5661 | 0.7524 |
354
+ | 0.3541 | 14.4286 | 606 | 0.5691 | 0.4368 | 0.5691 | 0.7544 |
355
+
356
+
357
+ ### Framework versions
358
+
359
+ - Transformers 4.44.2
360
+ - Pytorch 2.4.0+cu118
361
+ - Datasets 2.21.0
362
+ - 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:f3423191be5919fa7d5812d663802ad556fedea2fc35a4bdcf2868f035eb1816
3
+ size 540799996
training_args.bin ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:fb93c9fda10e7985b0f4ce57ef160618f30979ffd8b8c555662ff84f93dd9ec1
3
+ size 5304