Hugging Face's logo

MayBashendy
/
ArabicNewSplits7_FineTuningAraBERT_run2_AugV5_k1_task7_organization

Text Classification
Transformers
Safetensors
bert
Generated from Trainer
Inference Endpoints
Model card Files Community
MayBashendy commited on
Commit
d157f1d
·
verified ·
1 Parent(s): b16a04f

Training in progress, step 500

Browse files
Files changed (4) hide show
  1. README.md +325 -0
  2. config.json +32 -0
  3. model.safetensors +3 -0
  4. training_args.bin +3 -0
README.md ADDED
@@ -0,0 +1,325 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ library_name: transformers
3
+ base_model: aubmindlab/bert-base-arabertv02
4
+ tags:
5
+ - generated_from_trainer
6
+ model-index:
7
+ - name: ArabicNewSplits7_FineTuningAraBERT_run1_AugV5_k20_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_FineTuningAraBERT_run1_AugV5_k20_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: 0.4811
19
+ - Qwk: 0.6254
20
+ - Mse: 0.4811
21
+ - Rmse: 0.6936
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 | 0.04 | 2 | 2.5990 | -0.0262 | 2.5990 | 1.6121 |
53
+ | No log | 0.08 | 4 | 1.4044 | 0.0540 | 1.4044 | 1.1851 |
54
+ | No log | 0.12 | 6 | 0.9351 | -0.0228 | 0.9351 | 0.9670 |
55
+ | No log | 0.16 | 8 | 0.9408 | -0.0860 | 0.9408 | 0.9700 |
56
+ | No log | 0.2 | 10 | 0.8959 | -0.0079 | 0.8959 | 0.9465 |
57
+ | No log | 0.24 | 12 | 0.8302 | -0.0027 | 0.8302 | 0.9111 |
58
+ | No log | 0.28 | 14 | 0.8096 | 0.0 | 0.8096 | 0.8998 |
59
+ | No log | 0.32 | 16 | 0.8459 | 0.0 | 0.8459 | 0.9198 |
60
+ | No log | 0.36 | 18 | 0.8157 | -0.0444 | 0.8157 | 0.9031 |
61
+ | No log | 0.4 | 20 | 0.7359 | 0.0717 | 0.7359 | 0.8578 |
62
+ | No log | 0.44 | 22 | 0.7123 | 0.2407 | 0.7123 | 0.8440 |
63
+ | No log | 0.48 | 24 | 0.6686 | 0.2963 | 0.6686 | 0.8177 |
64
+ | No log | 0.52 | 26 | 0.6946 | 0.2041 | 0.6946 | 0.8334 |
65
+ | No log | 0.56 | 28 | 0.9998 | 0.0975 | 0.9998 | 0.9999 |
66
+ | No log | 0.6 | 30 | 1.1047 | 0.1265 | 1.1047 | 1.0510 |
67
+ | No log | 0.64 | 32 | 0.9848 | 0.0651 | 0.9848 | 0.9924 |
68
+ | No log | 0.68 | 34 | 0.8076 | 0.1714 | 0.8076 | 0.8987 |
69
+ | No log | 0.72 | 36 | 0.6670 | 0.2412 | 0.6670 | 0.8167 |
70
+ | No log | 0.76 | 38 | 0.7052 | 0.3238 | 0.7052 | 0.8398 |
71
+ | No log | 0.8 | 40 | 0.7228 | 0.3099 | 0.7228 | 0.8502 |
72
+ | No log | 0.84 | 42 | 0.6196 | 0.3673 | 0.6196 | 0.7871 |
73
+ | No log | 0.88 | 44 | 0.5745 | 0.4709 | 0.5745 | 0.7579 |
74
+ | No log | 0.92 | 46 | 0.5651 | 0.4538 | 0.5651 | 0.7517 |
75
+ | No log | 0.96 | 48 | 0.5628 | 0.5470 | 0.5628 | 0.7502 |
76
+ | No log | 1.0 | 50 | 0.7374 | 0.3693 | 0.7374 | 0.8587 |
77
+ | No log | 1.04 | 52 | 1.0917 | 0.2214 | 1.0917 | 1.0449 |
78
+ | No log | 1.08 | 54 | 1.1289 | 0.2439 | 1.1289 | 1.0625 |
79
+ | No log | 1.12 | 56 | 0.9952 | 0.2658 | 0.9952 | 0.9976 |
80
+ | No log | 1.16 | 58 | 0.9210 | 0.2273 | 0.9210 | 0.9597 |
81
+ | No log | 1.2 | 60 | 0.8071 | 0.2817 | 0.8071 | 0.8984 |
82
+ | No log | 1.24 | 62 | 0.6367 | 0.3829 | 0.6367 | 0.7979 |
83
+ | No log | 1.28 | 64 | 0.6022 | 0.3633 | 0.6022 | 0.7760 |
84
+ | No log | 1.32 | 66 | 0.5991 | 0.2641 | 0.5991 | 0.7740 |
85
+ | No log | 1.3600 | 68 | 0.5737 | 0.4007 | 0.5737 | 0.7574 |
86
+ | No log | 1.4 | 70 | 0.5645 | 0.4238 | 0.5645 | 0.7514 |
87
+ | No log | 1.44 | 72 | 0.5500 | 0.3274 | 0.5500 | 0.7416 |
88
+ | No log | 1.48 | 74 | 0.5848 | 0.2817 | 0.5848 | 0.7647 |
89
+ | No log | 1.52 | 76 | 0.6112 | 0.2851 | 0.6112 | 0.7818 |
90
+ | No log | 1.56 | 78 | 0.6345 | 0.3506 | 0.6345 | 0.7965 |
91
+ | No log | 1.6 | 80 | 0.6331 | 0.3477 | 0.6331 | 0.7957 |
92
+ | No log | 1.6400 | 82 | 0.6273 | 0.3446 | 0.6273 | 0.7920 |
93
+ | No log | 1.6800 | 84 | 0.6045 | 0.2890 | 0.6045 | 0.7775 |
94
+ | No log | 1.72 | 86 | 0.6001 | 0.2890 | 0.6001 | 0.7747 |
95
+ | No log | 1.76 | 88 | 0.6040 | 0.3866 | 0.6040 | 0.7772 |
96
+ | No log | 1.8 | 90 | 0.6018 | 0.3701 | 0.6018 | 0.7757 |
97
+ | No log | 1.8400 | 92 | 0.5701 | 0.4729 | 0.5701 | 0.7551 |
98
+ | No log | 1.88 | 94 | 0.5895 | 0.4677 | 0.5895 | 0.7678 |
99
+ | No log | 1.92 | 96 | 0.6273 | 0.4537 | 0.6273 | 0.7920 |
100
+ | No log | 1.96 | 98 | 0.6172 | 0.4969 | 0.6172 | 0.7856 |
101
+ | No log | 2.0 | 100 | 0.5122 | 0.4358 | 0.5122 | 0.7157 |
102
+ | No log | 2.04 | 102 | 0.5277 | 0.4855 | 0.5277 | 0.7264 |
103
+ | No log | 2.08 | 104 | 0.5261 | 0.4769 | 0.5261 | 0.7253 |
104
+ | No log | 2.12 | 106 | 0.5057 | 0.4973 | 0.5057 | 0.7111 |
105
+ | No log | 2.16 | 108 | 0.6185 | 0.5267 | 0.6185 | 0.7865 |
106
+ | No log | 2.2 | 110 | 0.8140 | 0.5167 | 0.8140 | 0.9022 |
107
+ | No log | 2.24 | 112 | 0.8148 | 0.4993 | 0.8148 | 0.9027 |
108
+ | No log | 2.2800 | 114 | 0.8405 | 0.3942 | 0.8405 | 0.9168 |
109
+ | No log | 2.32 | 116 | 0.7284 | 0.4383 | 0.7284 | 0.8535 |
110
+ | No log | 2.36 | 118 | 0.5738 | 0.5400 | 0.5738 | 0.7575 |
111
+ | No log | 2.4 | 120 | 0.4916 | 0.5022 | 0.4916 | 0.7012 |
112
+ | No log | 2.44 | 122 | 0.6215 | 0.4648 | 0.6215 | 0.7883 |
113
+ | No log | 2.48 | 124 | 0.6748 | 0.4716 | 0.6748 | 0.8215 |
114
+ | No log | 2.52 | 126 | 0.6089 | 0.4568 | 0.6089 | 0.7803 |
115
+ | No log | 2.56 | 128 | 0.5695 | 0.5050 | 0.5695 | 0.7546 |
116
+ | No log | 2.6 | 130 | 0.5416 | 0.4817 | 0.5416 | 0.7360 |
117
+ | No log | 2.64 | 132 | 0.5570 | 0.5117 | 0.5570 | 0.7463 |
118
+ | No log | 2.68 | 134 | 0.6157 | 0.6154 | 0.6157 | 0.7847 |
119
+ | No log | 2.7200 | 136 | 0.5799 | 0.6154 | 0.5799 | 0.7615 |
120
+ | No log | 2.76 | 138 | 0.5327 | 0.5589 | 0.5327 | 0.7299 |
121
+ | No log | 2.8 | 140 | 0.6589 | 0.5614 | 0.6589 | 0.8117 |
122
+ | No log | 2.84 | 142 | 0.7491 | 0.4199 | 0.7491 | 0.8655 |
123
+ | No log | 2.88 | 144 | 0.6992 | 0.3976 | 0.6992 | 0.8362 |
124
+ | No log | 2.92 | 146 | 0.5918 | 0.4051 | 0.5918 | 0.7693 |
125
+ | No log | 2.96 | 148 | 0.5436 | 0.5463 | 0.5436 | 0.7373 |
126
+ | No log | 3.0 | 150 | 0.5437 | 0.4762 | 0.5437 | 0.7374 |
127
+ | No log | 3.04 | 152 | 0.5879 | 0.3890 | 0.5879 | 0.7668 |
128
+ | No log | 3.08 | 154 | 0.7041 | 0.3475 | 0.7041 | 0.8391 |
129
+ | No log | 3.12 | 156 | 0.7131 | 0.3475 | 0.7131 | 0.8445 |
130
+ | No log | 3.16 | 158 | 0.6058 | 0.3914 | 0.6058 | 0.7784 |
131
+ | No log | 3.2 | 160 | 0.5380 | 0.5357 | 0.5380 | 0.7335 |
132
+ | No log | 3.24 | 162 | 0.5585 | 0.5779 | 0.5585 | 0.7473 |
133
+ | No log | 3.2800 | 164 | 0.5977 | 0.5765 | 0.5977 | 0.7731 |
134
+ | No log | 3.32 | 166 | 0.6725 | 0.5441 | 0.6725 | 0.8201 |
135
+ | No log | 3.36 | 168 | 0.7098 | 0.5441 | 0.7098 | 0.8425 |
136
+ | No log | 3.4 | 170 | 0.7040 | 0.5441 | 0.7040 | 0.8390 |
137
+ | No log | 3.44 | 172 | 0.5852 | 0.6195 | 0.5852 | 0.7650 |
138
+ | No log | 3.48 | 174 | 0.5389 | 0.5257 | 0.5389 | 0.7341 |
139
+ | No log | 3.52 | 176 | 0.5357 | 0.5067 | 0.5357 | 0.7319 |
140
+ | No log | 3.56 | 178 | 0.5520 | 0.5826 | 0.5520 | 0.7430 |
141
+ | No log | 3.6 | 180 | 0.6259 | 0.5696 | 0.6259 | 0.7911 |
142
+ | No log | 3.64 | 182 | 0.6048 | 0.5500 | 0.6048 | 0.7777 |
143
+ | No log | 3.68 | 184 | 0.5248 | 0.5826 | 0.5248 | 0.7244 |
144
+ | No log | 3.7200 | 186 | 0.5460 | 0.5157 | 0.5460 | 0.7389 |
145
+ | No log | 3.76 | 188 | 0.6738 | 0.3826 | 0.6738 | 0.8209 |
146
+ | No log | 3.8 | 190 | 0.6899 | 0.3867 | 0.6899 | 0.8306 |
147
+ | No log | 3.84 | 192 | 0.6321 | 0.4784 | 0.6321 | 0.7951 |
148
+ | No log | 3.88 | 194 | 0.5668 | 0.4505 | 0.5668 | 0.7529 |
149
+ | No log | 3.92 | 196 | 0.5668 | 0.4920 | 0.5668 | 0.7528 |
150
+ | No log | 3.96 | 198 | 0.5686 | 0.5870 | 0.5686 | 0.7541 |
151
+ | No log | 4.0 | 200 | 0.5665 | 0.5847 | 0.5665 | 0.7527 |
152
+ | No log | 4.04 | 202 | 0.5556 | 0.5377 | 0.5556 | 0.7454 |
153
+ | No log | 4.08 | 204 | 0.5692 | 0.4374 | 0.5692 | 0.7544 |
154
+ | No log | 4.12 | 206 | 0.5659 | 0.4374 | 0.5659 | 0.7522 |
155
+ | No log | 4.16 | 208 | 0.5562 | 0.4374 | 0.5562 | 0.7458 |
156
+ | No log | 4.2 | 210 | 0.5285 | 0.4881 | 0.5285 | 0.7270 |
157
+ | No log | 4.24 | 212 | 0.5824 | 0.5603 | 0.5824 | 0.7631 |
158
+ | No log | 4.28 | 214 | 0.6151 | 0.5475 | 0.6151 | 0.7843 |
159
+ | No log | 4.32 | 216 | 0.5903 | 0.5780 | 0.5903 | 0.7683 |
160
+ | No log | 4.36 | 218 | 0.6453 | 0.5752 | 0.6453 | 0.8033 |
161
+ | No log | 4.4 | 220 | 0.5607 | 0.5687 | 0.5607 | 0.7488 |
162
+ | No log | 4.44 | 222 | 0.5350 | 0.5728 | 0.5350 | 0.7314 |
163
+ | No log | 4.48 | 224 | 0.5496 | 0.5848 | 0.5496 | 0.7414 |
164
+ | No log | 4.52 | 226 | 0.5409 | 0.5872 | 0.5409 | 0.7354 |
165
+ | No log | 4.5600 | 228 | 0.5237 | 0.5949 | 0.5237 | 0.7237 |
166
+ | No log | 4.6 | 230 | 0.5248 | 0.5334 | 0.5248 | 0.7244 |
167
+ | No log | 4.64 | 232 | 0.5210 | 0.5257 | 0.5210 | 0.7218 |
168
+ | No log | 4.68 | 234 | 0.5067 | 0.5926 | 0.5067 | 0.7119 |
169
+ | No log | 4.72 | 236 | 0.5031 | 0.6235 | 0.5031 | 0.7093 |
170
+ | No log | 4.76 | 238 | 0.4870 | 0.5915 | 0.4870 | 0.6979 |
171
+ | No log | 4.8 | 240 | 0.4945 | 0.5272 | 0.4945 | 0.7032 |
172
+ | No log | 4.84 | 242 | 0.5205 | 0.5457 | 0.5205 | 0.7215 |
173
+ | No log | 4.88 | 244 | 0.5114 | 0.5668 | 0.5114 | 0.7151 |
174
+ | No log | 4.92 | 246 | 0.4872 | 0.5625 | 0.4872 | 0.6980 |
175
+ | No log | 4.96 | 248 | 0.4945 | 0.6345 | 0.4945 | 0.7032 |
176
+ | No log | 5.0 | 250 | 0.4807 | 0.6040 | 0.4807 | 0.6933 |
177
+ | No log | 5.04 | 252 | 0.4703 | 0.5625 | 0.4703 | 0.6858 |
178
+ | No log | 5.08 | 254 | 0.4646 | 0.5430 | 0.4646 | 0.6817 |
179
+ | No log | 5.12 | 256 | 0.4718 | 0.5538 | 0.4718 | 0.6869 |
180
+ | No log | 5.16 | 258 | 0.4520 | 0.6305 | 0.4520 | 0.6723 |
181
+ | No log | 5.2 | 260 | 0.4484 | 0.5268 | 0.4484 | 0.6696 |
182
+ | No log | 5.24 | 262 | 0.4439 | 0.5344 | 0.4439 | 0.6662 |
183
+ | No log | 5.28 | 264 | 0.4495 | 0.4929 | 0.4495 | 0.6704 |
184
+ | No log | 5.32 | 266 | 0.4525 | 0.5003 | 0.4525 | 0.6727 |
185
+ | No log | 5.36 | 268 | 0.4494 | 0.5367 | 0.4494 | 0.6704 |
186
+ | No log | 5.4 | 270 | 0.4818 | 0.5907 | 0.4818 | 0.6942 |
187
+ | No log | 5.44 | 272 | 0.4655 | 0.5933 | 0.4655 | 0.6823 |
188
+ | No log | 5.48 | 274 | 0.4359 | 0.5361 | 0.4359 | 0.6602 |
189
+ | No log | 5.52 | 276 | 0.4394 | 0.5890 | 0.4394 | 0.6629 |
190
+ | No log | 5.5600 | 278 | 0.4422 | 0.5719 | 0.4422 | 0.6650 |
191
+ | No log | 5.6 | 280 | 0.4516 | 0.5768 | 0.4516 | 0.6720 |
192
+ | No log | 5.64 | 282 | 0.4454 | 0.6426 | 0.4454 | 0.6674 |
193
+ | No log | 5.68 | 284 | 0.4668 | 0.6431 | 0.4668 | 0.6833 |
194
+ | No log | 5.72 | 286 | 0.6239 | 0.5468 | 0.6239 | 0.7898 |
195
+ | No log | 5.76 | 288 | 0.6078 | 0.5455 | 0.6078 | 0.7796 |
196
+ | No log | 5.8 | 290 | 0.4808 | 0.6445 | 0.4808 | 0.6934 |
197
+ | No log | 5.84 | 292 | 0.4642 | 0.6145 | 0.4642 | 0.6813 |
198
+ | No log | 5.88 | 294 | 0.5272 | 0.5357 | 0.5272 | 0.7261 |
199
+ | No log | 5.92 | 296 | 0.4989 | 0.5357 | 0.4989 | 0.7063 |
200
+ | No log | 5.96 | 298 | 0.4542 | 0.5926 | 0.4542 | 0.6740 |
201
+ | No log | 6.0 | 300 | 0.4525 | 0.6040 | 0.4525 | 0.6726 |
202
+ | No log | 6.04 | 302 | 0.4490 | 0.6223 | 0.4490 | 0.6701 |
203
+ | No log | 6.08 | 304 | 0.4631 | 0.6972 | 0.4631 | 0.6805 |
204
+ | No log | 6.12 | 306 | 0.4306 | 0.6407 | 0.4306 | 0.6562 |
205
+ | No log | 6.16 | 308 | 0.4512 | 0.5831 | 0.4512 | 0.6717 |
206
+ | No log | 6.2 | 310 | 0.5504 | 0.5598 | 0.5504 | 0.7419 |
207
+ | No log | 6.24 | 312 | 0.5272 | 0.5940 | 0.5272 | 0.7261 |
208
+ | No log | 6.28 | 314 | 0.4439 | 0.6434 | 0.4439 | 0.6662 |
209
+ | No log | 6.32 | 316 | 0.4850 | 0.6104 | 0.4850 | 0.6964 |
210
+ | No log | 6.36 | 318 | 0.5828 | 0.5643 | 0.5828 | 0.7634 |
211
+ | No log | 6.4 | 320 | 0.5720 | 0.6144 | 0.5720 | 0.7563 |
212
+ | No log | 6.44 | 322 | 0.4970 | 0.6546 | 0.4970 | 0.7050 |
213
+ | No log | 6.48 | 324 | 0.4883 | 0.6639 | 0.4883 | 0.6988 |
214
+ | No log | 6.52 | 326 | 0.4868 | 0.6469 | 0.4868 | 0.6977 |
215
+ | No log | 6.5600 | 328 | 0.4612 | 0.5614 | 0.4612 | 0.6791 |
216
+ | No log | 6.6 | 330 | 0.4902 | 0.6620 | 0.4902 | 0.7002 |
217
+ | No log | 6.64 | 332 | 0.5306 | 0.6294 | 0.5306 | 0.7284 |
218
+ | No log | 6.68 | 334 | 0.4990 | 0.6342 | 0.4990 | 0.7064 |
219
+ | No log | 6.72 | 336 | 0.4734 | 0.5933 | 0.4734 | 0.6881 |
220
+ | No log | 6.76 | 338 | 0.4501 | 0.5826 | 0.4501 | 0.6709 |
221
+ | No log | 6.8 | 340 | 0.4396 | 0.5826 | 0.4396 | 0.6630 |
222
+ | No log | 6.84 | 342 | 0.4633 | 0.6431 | 0.4633 | 0.6807 |
223
+ | No log | 6.88 | 344 | 0.5544 | 0.6144 | 0.5544 | 0.7446 |
224
+ | No log | 6.92 | 346 | 0.6483 | 0.5765 | 0.6483 | 0.8051 |
225
+ | No log | 6.96 | 348 | 0.5967 | 0.5970 | 0.5967 | 0.7725 |
226
+ | No log | 7.0 | 350 | 0.5432 | 0.6077 | 0.5432 | 0.7370 |
227
+ | No log | 7.04 | 352 | 0.5536 | 0.5970 | 0.5536 | 0.7440 |
228
+ | No log | 7.08 | 354 | 0.5426 | 0.6042 | 0.5426 | 0.7366 |
229
+ | No log | 7.12 | 356 | 0.5111 | 0.6042 | 0.5111 | 0.7149 |
230
+ | No log | 7.16 | 358 | 0.4855 | 0.6104 | 0.4855 | 0.6968 |
231
+ | No log | 7.2 | 360 | 0.4462 | 0.6020 | 0.4462 | 0.6680 |
232
+ | No log | 7.24 | 362 | 0.4425 | 0.6170 | 0.4425 | 0.6652 |
233
+ | No log | 7.28 | 364 | 0.4534 | 0.6210 | 0.4534 | 0.6734 |
234
+ | No log | 7.32 | 366 | 0.5497 | 0.6042 | 0.5497 | 0.7414 |
235
+ | No log | 7.36 | 368 | 0.6766 | 0.5700 | 0.6766 | 0.8225 |
236
+ | No log | 7.4 | 370 | 0.6142 | 0.5900 | 0.6142 | 0.7837 |
237
+ | No log | 7.44 | 372 | 0.4805 | 0.5569 | 0.4805 | 0.6932 |
238
+ | No log | 7.48 | 374 | 0.4642 | 0.5071 | 0.4642 | 0.6813 |
239
+ | No log | 7.52 | 376 | 0.4785 | 0.5411 | 0.4785 | 0.6917 |
240
+ | No log | 7.5600 | 378 | 0.4691 | 0.5640 | 0.4691 | 0.6849 |
241
+ | No log | 7.6 | 380 | 0.4755 | 0.5993 | 0.4755 | 0.6896 |
242
+ | No log | 7.64 | 382 | 0.4805 | 0.5765 | 0.4805 | 0.6932 |
243
+ | No log | 7.68 | 384 | 0.4886 | 0.5422 | 0.4886 | 0.6990 |
244
+ | No log | 7.72 | 386 | 0.5316 | 0.5017 | 0.5316 | 0.7291 |
245
+ | No log | 7.76 | 388 | 0.5655 | 0.4247 | 0.5655 | 0.7520 |
246
+ | No log | 7.8 | 390 | 0.5698 | 0.4513 | 0.5698 | 0.7549 |
247
+ | No log | 7.84 | 392 | 0.5979 | 0.5123 | 0.5979 | 0.7732 |
248
+ | No log | 7.88 | 394 | 0.6174 | 0.4904 | 0.6174 | 0.7857 |
249
+ | No log | 7.92 | 396 | 0.5357 | 0.5032 | 0.5357 | 0.7319 |
250
+ | No log | 7.96 | 398 | 0.4897 | 0.5413 | 0.4897 | 0.6998 |
251
+ | No log | 8.0 | 400 | 0.4922 | 0.6667 | 0.4922 | 0.7016 |
252
+ | No log | 8.04 | 402 | 0.4876 | 0.5860 | 0.4876 | 0.6983 |
253
+ | No log | 8.08 | 404 | 0.5099 | 0.5256 | 0.5099 | 0.7141 |
254
+ | No log | 8.12 | 406 | 0.4993 | 0.5632 | 0.4993 | 0.7066 |
255
+ | No log | 8.16 | 408 | 0.4773 | 0.5413 | 0.4773 | 0.6909 |
256
+ | No log | 8.2 | 410 | 0.4859 | 0.6068 | 0.4859 | 0.6970 |
257
+ | No log | 8.24 | 412 | 0.4865 | 0.5475 | 0.4865 | 0.6975 |
258
+ | No log | 8.28 | 414 | 0.4983 | 0.5422 | 0.4983 | 0.7059 |
259
+ | No log | 8.32 | 416 | 0.6146 | 0.4556 | 0.6146 | 0.7840 |
260
+ | No log | 8.36 | 418 | 0.6660 | 0.4992 | 0.6660 | 0.8161 |
261
+ | No log | 8.4 | 420 | 0.6121 | 0.4631 | 0.6121 | 0.7824 |
262
+ | No log | 8.44 | 422 | 0.5085 | 0.5289 | 0.5085 | 0.7131 |
263
+ | No log | 8.48 | 424 | 0.4731 | 0.5665 | 0.4731 | 0.6878 |
264
+ | No log | 8.52 | 426 | 0.4686 | 0.5440 | 0.4686 | 0.6845 |
265
+ | No log | 8.56 | 428 | 0.4788 | 0.5170 | 0.4788 | 0.6919 |
266
+ | No log | 8.6 | 430 | 0.5080 | 0.4502 | 0.5080 | 0.7127 |
267
+ | No log | 8.64 | 432 | 0.5425 | 0.4502 | 0.5425 | 0.7365 |
268
+ | No log | 8.68 | 434 | 0.5380 | 0.4502 | 0.5380 | 0.7335 |
269
+ | No log | 8.72 | 436 | 0.5006 | 0.5708 | 0.5006 | 0.7075 |
270
+ | No log | 8.76 | 438 | 0.4815 | 0.6743 | 0.4815 | 0.6939 |
271
+ | No log | 8.8 | 440 | 0.5323 | 0.6712 | 0.5323 | 0.7296 |
272
+ | No log | 8.84 | 442 | 0.5315 | 0.6784 | 0.5315 | 0.7290 |
273
+ | No log | 8.88 | 444 | 0.4997 | 0.6559 | 0.4997 | 0.7069 |
274
+ | No log | 8.92 | 446 | 0.4984 | 0.5933 | 0.4984 | 0.7060 |
275
+ | No log | 8.96 | 448 | 0.4910 | 0.5996 | 0.4910 | 0.7007 |
276
+ | No log | 9.0 | 450 | 0.4778 | 0.5974 | 0.4778 | 0.6912 |
277
+ | No log | 9.04 | 452 | 0.4684 | 0.5798 | 0.4684 | 0.6844 |
278
+ | No log | 9.08 | 454 | 0.5016 | 0.5682 | 0.5016 | 0.7083 |
279
+ | No log | 9.12 | 456 | 0.4943 | 0.6096 | 0.4943 | 0.7031 |
280
+ | No log | 9.16 | 458 | 0.4806 | 0.6592 | 0.4806 | 0.6933 |
281
+ | No log | 9.2 | 460 | 0.5117 | 0.6612 | 0.5117 | 0.7153 |
282
+ | No log | 9.24 | 462 | 0.5565 | 0.5696 | 0.5565 | 0.7460 |
283
+ | No log | 9.28 | 464 | 0.5807 | 0.5328 | 0.5807 | 0.7621 |
284
+ | No log | 9.32 | 466 | 0.5006 | 0.6701 | 0.5006 | 0.7075 |
285
+ | No log | 9.36 | 468 | 0.4623 | 0.5413 | 0.4623 | 0.6799 |
286
+ | No log | 9.4 | 470 | 0.5548 | 0.4997 | 0.5548 | 0.7449 |
287
+ | No log | 9.44 | 472 | 0.5841 | 0.4664 | 0.5841 | 0.7643 |
288
+ | No log | 9.48 | 474 | 0.5131 | 0.4705 | 0.5131 | 0.7163 |
289
+ | No log | 9.52 | 476 | 0.4719 | 0.5250 | 0.4719 | 0.6869 |
290
+ | No log | 9.56 | 478 | 0.4737 | 0.5915 | 0.4737 | 0.6883 |
291
+ | No log | 9.6 | 480 | 0.4757 | 0.5846 | 0.4757 | 0.6897 |
292
+ | No log | 9.64 | 482 | 0.4958 | 0.5473 | 0.4958 | 0.7041 |
293
+ | No log | 9.68 | 484 | 0.5260 | 0.5619 | 0.5260 | 0.7252 |
294
+ | No log | 9.72 | 486 | 0.5021 | 0.5619 | 0.5021 | 0.7086 |
295
+ | No log | 9.76 | 488 | 0.4793 | 0.6371 | 0.4793 | 0.6923 |
296
+ | No log | 9.8 | 490 | 0.4602 | 0.6460 | 0.4602 | 0.6784 |
297
+ | No log | 9.84 | 492 | 0.4503 | 0.6078 | 0.4503 | 0.6711 |
298
+ | No log | 9.88 | 494 | 0.4452 | 0.5874 | 0.4452 | 0.6672 |
299
+ | No log | 9.92 | 496 | 0.4350 | 0.6156 | 0.4350 | 0.6595 |
300
+ | No log | 9.96 | 498 | 0.4248 | 0.6567 | 0.4248 | 0.6518 |
301
+ | 0.3868 | 10.0 | 500 | 0.4396 | 0.6601 | 0.4396 | 0.6630 |
302
+ | 0.3868 | 10.04 | 502 | 0.4502 | 0.6705 | 0.4502 | 0.6710 |
303
+ | 0.3868 | 10.08 | 504 | 0.4714 | 0.5922 | 0.4714 | 0.6866 |
304
+ | 0.3868 | 10.12 | 506 | 0.5153 | 0.5778 | 0.5153 | 0.7178 |
305
+ | 0.3868 | 10.16 | 508 | 0.5229 | 0.5778 | 0.5229 | 0.7231 |
306
+ | 0.3868 | 10.2 | 510 | 0.4758 | 0.6624 | 0.4758 | 0.6898 |
307
+ | 0.3868 | 10.24 | 512 | 0.4528 | 0.6501 | 0.4528 | 0.6729 |
308
+ | 0.3868 | 10.28 | 514 | 0.4665 | 0.6612 | 0.4665 | 0.6830 |
309
+ | 0.3868 | 10.32 | 516 | 0.4798 | 0.6342 | 0.4798 | 0.6927 |
310
+ | 0.3868 | 10.36 | 518 | 0.5197 | 0.6373 | 0.5197 | 0.7209 |
311
+ | 0.3868 | 10.4 | 520 | 0.4911 | 0.6427 | 0.4911 | 0.7008 |
312
+ | 0.3868 | 10.44 | 522 | 0.4555 | 0.6690 | 0.4555 | 0.6749 |
313
+ | 0.3868 | 10.48 | 524 | 0.4752 | 0.5899 | 0.4752 | 0.6894 |
314
+ | 0.3868 | 10.52 | 526 | 0.5003 | 0.5501 | 0.5003 | 0.7073 |
315
+ | 0.3868 | 10.56 | 528 | 0.5087 | 0.5692 | 0.5087 | 0.7132 |
316
+ | 0.3868 | 10.6 | 530 | 0.5013 | 0.5692 | 0.5013 | 0.7080 |
317
+ | 0.3868 | 10.64 | 532 | 0.4811 | 0.6254 | 0.4811 | 0.6936 |
318
+
319
+
320
+ ### Framework versions
321
+
322
+ - Transformers 4.44.2
323
+ - Pytorch 2.4.0+cu118
324
+ - Datasets 2.21.0
325
+ - 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 sha256:2167b71939c1256095ebf103d8ec6a135f6f7c9c4769e76131afbf1f77eebf6c
3
+ size 540799996
training_args.bin ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:a5f97dbb47ff7a19c6d865dc5e6c91ddaaa8bdc7967e8b3c2bf6bcf71eaaa492
3
+ size 5240