MayBashendy commited on
Commit
8018d36
·
verified ·
1 Parent(s): 97d97c4

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_OSS_usingWellWrittenEssays_FineTuningAraBERT_run1_AugV5_k15_task1_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_OSS_usingWellWrittenEssays_FineTuningAraBERT_run1_AugV5_k15_task1_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: 0.8033
19
+ - Qwk: 0.7105
20
+ - Mse: 0.8033
21
+ - Rmse: 0.8963
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 | 0.0179 | 2 | 7.0692 | 0.0290 | 7.0692 | 2.6588 |
53
+ | No log | 0.0357 | 4 | 4.1574 | 0.1053 | 4.1574 | 2.0390 |
54
+ | No log | 0.0536 | 6 | 2.5318 | 0.0870 | 2.5318 | 1.5912 |
55
+ | No log | 0.0714 | 8 | 1.8752 | 0.2276 | 1.8752 | 1.3694 |
56
+ | No log | 0.0893 | 10 | 1.6967 | 0.2689 | 1.6967 | 1.3026 |
57
+ | No log | 0.1071 | 12 | 1.5431 | 0.1835 | 1.5431 | 1.2422 |
58
+ | No log | 0.125 | 14 | 1.4600 | 0.2456 | 1.4600 | 1.2083 |
59
+ | No log | 0.1429 | 16 | 1.4900 | 0.3279 | 1.4900 | 1.2207 |
60
+ | No log | 0.1607 | 18 | 1.6387 | 0.4211 | 1.6387 | 1.2801 |
61
+ | No log | 0.1786 | 20 | 1.0393 | 0.4923 | 1.0393 | 1.0195 |
62
+ | No log | 0.1964 | 22 | 1.2822 | 0.4882 | 1.2822 | 1.1324 |
63
+ | No log | 0.2143 | 24 | 1.5578 | 0.3559 | 1.5578 | 1.2481 |
64
+ | No log | 0.2321 | 26 | 1.4560 | 0.3304 | 1.4560 | 1.2066 |
65
+ | No log | 0.25 | 28 | 1.2691 | 0.3684 | 1.2691 | 1.1266 |
66
+ | No log | 0.2679 | 30 | 1.1808 | 0.4463 | 1.1808 | 1.0867 |
67
+ | No log | 0.2857 | 32 | 1.4781 | 0.4828 | 1.4781 | 1.2158 |
68
+ | No log | 0.3036 | 34 | 1.5579 | 0.4837 | 1.5579 | 1.2482 |
69
+ | No log | 0.3214 | 36 | 1.1682 | 0.6309 | 1.1682 | 1.0808 |
70
+ | No log | 0.3393 | 38 | 0.8417 | 0.6809 | 0.8417 | 0.9174 |
71
+ | No log | 0.3571 | 40 | 0.9560 | 0.6620 | 0.9560 | 0.9777 |
72
+ | No log | 0.375 | 42 | 1.2008 | 0.4895 | 1.2008 | 1.0958 |
73
+ | No log | 0.3929 | 44 | 1.2513 | 0.4722 | 1.2513 | 1.1186 |
74
+ | No log | 0.4107 | 46 | 1.1753 | 0.5143 | 1.1753 | 1.0841 |
75
+ | No log | 0.4286 | 48 | 1.1084 | 0.5821 | 1.1084 | 1.0528 |
76
+ | No log | 0.4464 | 50 | 1.1309 | 0.5926 | 1.1309 | 1.0634 |
77
+ | No log | 0.4643 | 52 | 1.0382 | 0.6575 | 1.0382 | 1.0189 |
78
+ | No log | 0.4821 | 54 | 1.1589 | 0.5974 | 1.1589 | 1.0765 |
79
+ | No log | 0.5 | 56 | 1.5396 | 0.5422 | 1.5396 | 1.2408 |
80
+ | No log | 0.5179 | 58 | 1.3346 | 0.5375 | 1.3346 | 1.1552 |
81
+ | No log | 0.5357 | 60 | 0.9809 | 0.5921 | 0.9809 | 0.9904 |
82
+ | No log | 0.5536 | 62 | 0.8371 | 0.6622 | 0.8371 | 0.9149 |
83
+ | No log | 0.5714 | 64 | 0.8265 | 0.7273 | 0.8265 | 0.9091 |
84
+ | No log | 0.5893 | 66 | 0.9889 | 0.6232 | 0.9889 | 0.9945 |
85
+ | No log | 0.6071 | 68 | 1.0932 | 0.5970 | 1.0932 | 1.0455 |
86
+ | No log | 0.625 | 70 | 1.0503 | 0.6043 | 1.0503 | 1.0248 |
87
+ | No log | 0.6429 | 72 | 1.0452 | 0.5874 | 1.0452 | 1.0223 |
88
+ | No log | 0.6607 | 74 | 1.0060 | 0.5986 | 1.0060 | 1.0030 |
89
+ | No log | 0.6786 | 76 | 0.8557 | 0.6986 | 0.8557 | 0.9250 |
90
+ | No log | 0.6964 | 78 | 0.9999 | 0.6176 | 0.9999 | 1.0000 |
91
+ | No log | 0.7143 | 80 | 1.1681 | 0.4252 | 1.1681 | 1.0808 |
92
+ | No log | 0.7321 | 82 | 0.9668 | 0.6619 | 0.9668 | 0.9833 |
93
+ | No log | 0.75 | 84 | 0.8337 | 0.6667 | 0.8337 | 0.9131 |
94
+ | No log | 0.7679 | 86 | 0.9275 | 0.7073 | 0.9275 | 0.9631 |
95
+ | No log | 0.7857 | 88 | 0.9425 | 0.6538 | 0.9425 | 0.9708 |
96
+ | No log | 0.8036 | 90 | 0.9628 | 0.6531 | 0.9628 | 0.9812 |
97
+ | No log | 0.8214 | 92 | 1.0699 | 0.5957 | 1.0699 | 1.0343 |
98
+ | No log | 0.8393 | 94 | 0.9829 | 0.6176 | 0.9829 | 0.9914 |
99
+ | No log | 0.8571 | 96 | 0.8777 | 0.6479 | 0.8777 | 0.9369 |
100
+ | No log | 0.875 | 98 | 0.7797 | 0.7075 | 0.7797 | 0.8830 |
101
+ | No log | 0.8929 | 100 | 0.7751 | 0.7133 | 0.7751 | 0.8804 |
102
+ | No log | 0.9107 | 102 | 0.8517 | 0.6389 | 0.8517 | 0.9229 |
103
+ | No log | 0.9286 | 104 | 1.0168 | 0.6944 | 1.0168 | 1.0083 |
104
+ | No log | 0.9464 | 106 | 1.1986 | 0.5694 | 1.1986 | 1.0948 |
105
+ | No log | 0.9643 | 108 | 1.0878 | 0.6207 | 1.0878 | 1.0430 |
106
+ | No log | 0.9821 | 110 | 0.8883 | 0.6577 | 0.8883 | 0.9425 |
107
+ | No log | 1.0 | 112 | 0.8210 | 0.7285 | 0.8210 | 0.9061 |
108
+ | No log | 1.0179 | 114 | 0.7821 | 0.7067 | 0.7821 | 0.8844 |
109
+ | No log | 1.0357 | 116 | 0.8000 | 0.6974 | 0.8000 | 0.8944 |
110
+ | No log | 1.0536 | 118 | 1.0201 | 0.6626 | 1.0201 | 1.0100 |
111
+ | No log | 1.0714 | 120 | 1.1889 | 0.5868 | 1.1889 | 1.0904 |
112
+ | No log | 1.0893 | 122 | 1.0592 | 0.6420 | 1.0592 | 1.0292 |
113
+ | No log | 1.1071 | 124 | 0.9041 | 0.65 | 0.9041 | 0.9508 |
114
+ | No log | 1.125 | 126 | 0.9323 | 0.7241 | 0.9323 | 0.9656 |
115
+ | No log | 1.1429 | 128 | 1.0110 | 0.7243 | 1.0110 | 1.0055 |
116
+ | No log | 1.1607 | 130 | 1.0626 | 0.7083 | 1.0626 | 1.0308 |
117
+ | No log | 1.1786 | 132 | 1.1186 | 0.6848 | 1.1186 | 1.0576 |
118
+ | No log | 1.1964 | 134 | 1.1331 | 0.6703 | 1.1331 | 1.0645 |
119
+ | No log | 1.2143 | 136 | 1.0484 | 0.6588 | 1.0484 | 1.0239 |
120
+ | No log | 1.2321 | 138 | 1.1404 | 0.6272 | 1.1404 | 1.0679 |
121
+ | No log | 1.25 | 140 | 1.0964 | 0.6310 | 1.0964 | 1.0471 |
122
+ | No log | 1.2679 | 142 | 0.9691 | 0.6341 | 0.9691 | 0.9844 |
123
+ | No log | 1.2857 | 144 | 0.9084 | 0.7073 | 0.9084 | 0.9531 |
124
+ | No log | 1.3036 | 146 | 1.0605 | 0.6353 | 1.0605 | 1.0298 |
125
+ | No log | 1.3214 | 148 | 1.3467 | 0.6047 | 1.3467 | 1.1605 |
126
+ | No log | 1.3393 | 150 | 1.4350 | 0.5625 | 1.4350 | 1.1979 |
127
+ | No log | 1.3571 | 152 | 1.2285 | 0.5325 | 1.2285 | 1.1084 |
128
+ | No log | 1.375 | 154 | 0.9576 | 0.6383 | 0.9576 | 0.9786 |
129
+ | No log | 1.3929 | 156 | 0.8912 | 0.6809 | 0.8912 | 0.9440 |
130
+ | No log | 1.4107 | 158 | 0.9577 | 0.6531 | 0.9577 | 0.9786 |
131
+ | No log | 1.4286 | 160 | 1.0655 | 0.6076 | 1.0655 | 1.0322 |
132
+ | No log | 1.4464 | 162 | 0.9949 | 0.5974 | 0.9949 | 0.9975 |
133
+ | No log | 1.4643 | 164 | 0.9234 | 0.6835 | 0.9234 | 0.9609 |
134
+ | No log | 1.4821 | 166 | 0.8885 | 0.7066 | 0.8885 | 0.9426 |
135
+ | No log | 1.5 | 168 | 0.9899 | 0.6851 | 0.9899 | 0.9950 |
136
+ | No log | 1.5179 | 170 | 1.1720 | 0.6264 | 1.1720 | 1.0826 |
137
+ | No log | 1.5357 | 172 | 1.0951 | 0.5939 | 1.0951 | 1.0465 |
138
+ | No log | 1.5536 | 174 | 1.0808 | 0.6460 | 1.0808 | 1.0396 |
139
+ | No log | 1.5714 | 176 | 1.0237 | 0.6081 | 1.0237 | 1.0118 |
140
+ | No log | 1.5893 | 178 | 0.9893 | 0.6471 | 0.9893 | 0.9946 |
141
+ | No log | 1.6071 | 180 | 1.0784 | 0.6184 | 1.0784 | 1.0384 |
142
+ | No log | 1.625 | 182 | 1.1831 | 0.6154 | 1.1831 | 1.0877 |
143
+ | No log | 1.6429 | 184 | 1.1546 | 0.6154 | 1.1546 | 1.0745 |
144
+ | No log | 1.6607 | 186 | 0.9932 | 0.6708 | 0.9932 | 0.9966 |
145
+ | No log | 1.6786 | 188 | 0.8709 | 0.6846 | 0.8709 | 0.9332 |
146
+ | No log | 1.6964 | 190 | 0.7765 | 0.7532 | 0.7765 | 0.8812 |
147
+ | No log | 1.7143 | 192 | 0.7771 | 0.7532 | 0.7771 | 0.8815 |
148
+ | No log | 1.7321 | 194 | 0.9044 | 0.7117 | 0.9044 | 0.9510 |
149
+ | No log | 1.75 | 196 | 1.1437 | 0.6409 | 1.1437 | 1.0694 |
150
+ | No log | 1.7679 | 198 | 1.0917 | 0.6556 | 1.0917 | 1.0448 |
151
+ | No log | 1.7857 | 200 | 0.9767 | 0.6626 | 0.9767 | 0.9883 |
152
+ | No log | 1.8036 | 202 | 0.8497 | 0.7285 | 0.8497 | 0.9218 |
153
+ | No log | 1.8214 | 204 | 0.8482 | 0.6714 | 0.8482 | 0.9210 |
154
+ | No log | 1.8393 | 206 | 0.8927 | 0.6812 | 0.8927 | 0.9449 |
155
+ | No log | 1.8571 | 208 | 1.0477 | 0.6154 | 1.0477 | 1.0236 |
156
+ | No log | 1.875 | 210 | 1.1982 | 0.6047 | 1.1982 | 1.0946 |
157
+ | No log | 1.8929 | 212 | 1.1300 | 0.6552 | 1.1300 | 1.0630 |
158
+ | No log | 1.9107 | 214 | 0.8790 | 0.7073 | 0.8790 | 0.9376 |
159
+ | No log | 1.9286 | 216 | 0.7010 | 0.7771 | 0.7010 | 0.8372 |
160
+ | No log | 1.9464 | 218 | 0.6779 | 0.7692 | 0.6779 | 0.8233 |
161
+ | No log | 1.9643 | 220 | 0.7233 | 0.7662 | 0.7233 | 0.8505 |
162
+ | No log | 1.9821 | 222 | 0.8459 | 0.7051 | 0.8459 | 0.9197 |
163
+ | No log | 2.0 | 224 | 0.8773 | 0.7020 | 0.8773 | 0.9366 |
164
+ | No log | 2.0179 | 226 | 0.8465 | 0.7285 | 0.8465 | 0.9201 |
165
+ | No log | 2.0357 | 228 | 0.7425 | 0.7467 | 0.7425 | 0.8617 |
166
+ | No log | 2.0536 | 230 | 0.7274 | 0.7105 | 0.7274 | 0.8529 |
167
+ | No log | 2.0714 | 232 | 0.7615 | 0.7320 | 0.7615 | 0.8726 |
168
+ | No log | 2.0893 | 234 | 0.8968 | 0.7283 | 0.8968 | 0.9470 |
169
+ | No log | 2.1071 | 236 | 0.9328 | 0.7381 | 0.9328 | 0.9658 |
170
+ | No log | 2.125 | 238 | 0.9057 | 0.7067 | 0.9057 | 0.9517 |
171
+ | No log | 2.1429 | 240 | 0.9498 | 0.6389 | 0.9498 | 0.9746 |
172
+ | No log | 2.1607 | 242 | 0.9999 | 0.6027 | 0.9999 | 0.9999 |
173
+ | No log | 2.1786 | 244 | 0.9814 | 0.6043 | 0.9814 | 0.9907 |
174
+ | No log | 2.1964 | 246 | 0.9734 | 0.6418 | 0.9734 | 0.9866 |
175
+ | No log | 2.2143 | 248 | 1.0053 | 0.6277 | 1.0053 | 1.0027 |
176
+ | No log | 2.2321 | 250 | 1.0217 | 0.6040 | 1.0217 | 1.0108 |
177
+ | No log | 2.25 | 252 | 1.0977 | 0.6024 | 1.0977 | 1.0477 |
178
+ | No log | 2.2679 | 254 | 1.1427 | 0.5952 | 1.1427 | 1.0690 |
179
+ | No log | 2.2857 | 256 | 1.1740 | 0.6118 | 1.1740 | 1.0835 |
180
+ | No log | 2.3036 | 258 | 1.0900 | 0.6272 | 1.0900 | 1.0440 |
181
+ | No log | 2.3214 | 260 | 0.9967 | 0.6667 | 0.9967 | 0.9983 |
182
+ | No log | 2.3393 | 262 | 0.9220 | 0.6203 | 0.9220 | 0.9602 |
183
+ | No log | 2.3571 | 264 | 0.8856 | 0.7160 | 0.8856 | 0.9410 |
184
+ | No log | 2.375 | 266 | 0.7902 | 0.7403 | 0.7902 | 0.8889 |
185
+ | No log | 2.3929 | 268 | 0.7527 | 0.7625 | 0.7527 | 0.8676 |
186
+ | No log | 2.4107 | 270 | 0.8106 | 0.7458 | 0.8106 | 0.9003 |
187
+ | No log | 2.4286 | 272 | 1.0337 | 0.7273 | 1.0337 | 1.0167 |
188
+ | No log | 2.4464 | 274 | 1.0115 | 0.7579 | 1.0115 | 1.0057 |
189
+ | No log | 2.4643 | 276 | 0.8576 | 0.7081 | 0.8576 | 0.9261 |
190
+ | No log | 2.4821 | 278 | 0.8394 | 0.7179 | 0.8394 | 0.9162 |
191
+ | No log | 2.5 | 280 | 0.9278 | 0.6452 | 0.9278 | 0.9632 |
192
+ | No log | 2.5179 | 282 | 0.9965 | 0.6667 | 0.9965 | 0.9982 |
193
+ | No log | 2.5357 | 284 | 1.2587 | 0.6186 | 1.2587 | 1.1219 |
194
+ | No log | 2.5536 | 286 | 1.2133 | 0.5978 | 1.2133 | 1.1015 |
195
+ | No log | 2.5714 | 288 | 0.9821 | 0.6835 | 0.9821 | 0.9910 |
196
+ | No log | 2.5893 | 290 | 0.8502 | 0.7383 | 0.8502 | 0.9221 |
197
+ | No log | 2.6071 | 292 | 0.8478 | 0.75 | 0.8478 | 0.9208 |
198
+ | No log | 2.625 | 294 | 0.9359 | 0.7195 | 0.9359 | 0.9674 |
199
+ | No log | 2.6429 | 296 | 1.0299 | 0.6556 | 1.0299 | 1.0148 |
200
+ | No log | 2.6607 | 298 | 1.0466 | 0.6556 | 1.0466 | 1.0230 |
201
+ | No log | 2.6786 | 300 | 1.1088 | 0.6556 | 1.1088 | 1.0530 |
202
+ | No log | 2.6964 | 302 | 1.1680 | 0.6413 | 1.1680 | 1.0807 |
203
+ | No log | 2.7143 | 304 | 1.0561 | 0.6784 | 1.0561 | 1.0277 |
204
+ | No log | 2.7321 | 306 | 0.9354 | 0.7432 | 0.9354 | 0.9672 |
205
+ | No log | 2.75 | 308 | 0.9109 | 0.7183 | 0.9109 | 0.9544 |
206
+ | No log | 2.7679 | 310 | 0.8985 | 0.7355 | 0.8985 | 0.9479 |
207
+ | No log | 2.7857 | 312 | 0.8168 | 0.7484 | 0.8168 | 0.9038 |
208
+ | No log | 2.8036 | 314 | 0.8011 | 0.7702 | 0.8011 | 0.8951 |
209
+ | No log | 2.8214 | 316 | 0.8438 | 0.7529 | 0.8438 | 0.9186 |
210
+ | No log | 2.8393 | 318 | 1.0111 | 0.7263 | 1.0111 | 1.0055 |
211
+ | No log | 2.8571 | 320 | 1.3065 | 0.6146 | 1.3065 | 1.1430 |
212
+ | No log | 2.875 | 322 | 1.3572 | 0.5905 | 1.3572 | 1.1650 |
213
+ | No log | 2.8929 | 324 | 1.1395 | 0.6702 | 1.1395 | 1.0675 |
214
+ | No log | 2.9107 | 326 | 1.0308 | 0.6591 | 1.0308 | 1.0153 |
215
+ | No log | 2.9286 | 328 | 0.9712 | 0.6707 | 0.9712 | 0.9855 |
216
+ | No log | 2.9464 | 330 | 0.9833 | 0.6824 | 0.9833 | 0.9916 |
217
+ | No log | 2.9643 | 332 | 1.0393 | 0.6739 | 1.0393 | 1.0195 |
218
+ | No log | 2.9821 | 334 | 1.0743 | 0.6842 | 1.0743 | 1.0365 |
219
+ | No log | 3.0 | 336 | 1.0319 | 0.6932 | 1.0319 | 1.0158 |
220
+ | No log | 3.0179 | 338 | 1.0766 | 0.6552 | 1.0766 | 1.0376 |
221
+ | No log | 3.0357 | 340 | 1.0338 | 0.6587 | 1.0338 | 1.0167 |
222
+ | No log | 3.0536 | 342 | 0.9316 | 0.6835 | 0.9316 | 0.9652 |
223
+ | No log | 3.0714 | 344 | 0.8136 | 0.7347 | 0.8136 | 0.9020 |
224
+ | No log | 3.0893 | 346 | 0.7881 | 0.7516 | 0.7881 | 0.8878 |
225
+ | No log | 3.1071 | 348 | 0.7598 | 0.7407 | 0.7598 | 0.8717 |
226
+ | No log | 3.125 | 350 | 0.7927 | 0.7368 | 0.7927 | 0.8903 |
227
+ | No log | 3.1429 | 352 | 0.7632 | 0.7886 | 0.7632 | 0.8736 |
228
+ | No log | 3.1607 | 354 | 0.7183 | 0.7882 | 0.7183 | 0.8475 |
229
+ | No log | 3.1786 | 356 | 0.6946 | 0.7811 | 0.6946 | 0.8334 |
230
+ | No log | 3.1964 | 358 | 0.7320 | 0.7841 | 0.7320 | 0.8555 |
231
+ | No log | 3.2143 | 360 | 0.8528 | 0.7553 | 0.8528 | 0.9235 |
232
+ | No log | 3.2321 | 362 | 0.8944 | 0.7380 | 0.8944 | 0.9457 |
233
+ | No log | 3.25 | 364 | 0.8954 | 0.6905 | 0.8954 | 0.9462 |
234
+ | No log | 3.2679 | 366 | 0.9645 | 0.6786 | 0.9645 | 0.9821 |
235
+ | No log | 3.2857 | 368 | 1.0302 | 0.6471 | 1.0302 | 1.0150 |
236
+ | No log | 3.3036 | 370 | 1.0323 | 0.6509 | 1.0323 | 1.0160 |
237
+ | No log | 3.3214 | 372 | 0.9326 | 0.6842 | 0.9326 | 0.9657 |
238
+ | No log | 3.3393 | 374 | 0.8577 | 0.7027 | 0.8577 | 0.9261 |
239
+ | No log | 3.3571 | 376 | 0.8081 | 0.7260 | 0.8081 | 0.8990 |
240
+ | No log | 3.375 | 378 | 0.7742 | 0.7211 | 0.7742 | 0.8799 |
241
+ | No log | 3.3929 | 380 | 0.7897 | 0.7403 | 0.7897 | 0.8887 |
242
+ | No log | 3.4107 | 382 | 0.8103 | 0.7407 | 0.8103 | 0.9002 |
243
+ | No log | 3.4286 | 384 | 0.8122 | 0.7368 | 0.8122 | 0.9012 |
244
+ | No log | 3.4464 | 386 | 0.7503 | 0.7857 | 0.7503 | 0.8662 |
245
+ | No log | 3.4643 | 388 | 0.7171 | 0.8 | 0.7171 | 0.8468 |
246
+ | No log | 3.4821 | 390 | 0.7430 | 0.7683 | 0.7430 | 0.8620 |
247
+ | No log | 3.5 | 392 | 0.7633 | 0.7439 | 0.7633 | 0.8736 |
248
+ | No log | 3.5179 | 394 | 0.8321 | 0.7059 | 0.8321 | 0.9122 |
249
+ | No log | 3.5357 | 396 | 0.8466 | 0.7176 | 0.8466 | 0.9201 |
250
+ | No log | 3.5536 | 398 | 0.9649 | 0.7 | 0.9649 | 0.9823 |
251
+ | No log | 3.5714 | 400 | 1.0499 | 0.6776 | 1.0499 | 1.0246 |
252
+ | No log | 3.5893 | 402 | 1.0078 | 0.6587 | 1.0078 | 1.0039 |
253
+ | No log | 3.6071 | 404 | 1.0461 | 0.6463 | 1.0461 | 1.0228 |
254
+ | No log | 3.625 | 406 | 0.9749 | 0.6792 | 0.9749 | 0.9874 |
255
+ | No log | 3.6429 | 408 | 0.8030 | 0.6897 | 0.8030 | 0.8961 |
256
+ | No log | 3.6607 | 410 | 0.7392 | 0.6857 | 0.7392 | 0.8598 |
257
+ | No log | 3.6786 | 412 | 0.7389 | 0.6993 | 0.7389 | 0.8596 |
258
+ | No log | 3.6964 | 414 | 0.8146 | 0.7215 | 0.8146 | 0.9025 |
259
+ | No log | 3.7143 | 416 | 1.0191 | 0.6957 | 1.0191 | 1.0095 |
260
+ | No log | 3.7321 | 418 | 1.1366 | 0.6409 | 1.1366 | 1.0661 |
261
+ | No log | 3.75 | 420 | 1.0853 | 0.6275 | 1.0853 | 1.0418 |
262
+ | No log | 3.7679 | 422 | 1.0220 | 0.6667 | 1.0220 | 1.0109 |
263
+ | No log | 3.7857 | 424 | 0.9255 | 0.6849 | 0.9255 | 0.9620 |
264
+ | No log | 3.8036 | 426 | 0.8933 | 0.7097 | 0.8933 | 0.9452 |
265
+ | No log | 3.8214 | 428 | 0.9713 | 0.6548 | 0.9713 | 0.9856 |
266
+ | No log | 3.8393 | 430 | 0.9895 | 0.6595 | 0.9895 | 0.9947 |
267
+ | No log | 3.8571 | 432 | 1.0042 | 0.6595 | 1.0042 | 1.0021 |
268
+ | No log | 3.875 | 434 | 0.9775 | 0.6550 | 0.9775 | 0.9887 |
269
+ | No log | 3.8929 | 436 | 1.0521 | 0.6316 | 1.0521 | 1.0257 |
270
+ | No log | 3.9107 | 438 | 1.1280 | 0.6409 | 1.1280 | 1.0621 |
271
+ | No log | 3.9286 | 440 | 1.1044 | 0.6433 | 1.1044 | 1.0509 |
272
+ | No log | 3.9464 | 442 | 1.0860 | 0.6429 | 1.0860 | 1.0421 |
273
+ | No log | 3.9643 | 444 | 1.0181 | 0.6386 | 1.0181 | 1.0090 |
274
+ | No log | 3.9821 | 446 | 0.9526 | 0.6627 | 0.9526 | 0.9760 |
275
+ | No log | 4.0 | 448 | 0.8881 | 0.7421 | 0.8881 | 0.9424 |
276
+ | No log | 4.0179 | 450 | 0.9283 | 0.7079 | 0.9283 | 0.9635 |
277
+ | No log | 4.0357 | 452 | 1.0298 | 0.6557 | 1.0298 | 1.0148 |
278
+ | No log | 4.0536 | 454 | 1.1783 | 0.6736 | 1.1783 | 1.0855 |
279
+ | No log | 4.0714 | 456 | 1.2438 | 0.6162 | 1.2438 | 1.1152 |
280
+ | No log | 4.0893 | 458 | 1.0635 | 0.6753 | 1.0635 | 1.0313 |
281
+ | No log | 4.1071 | 460 | 0.9782 | 0.6812 | 0.9782 | 0.9891 |
282
+ | No log | 4.125 | 462 | 0.9827 | 0.6812 | 0.9827 | 0.9913 |
283
+ | No log | 4.1429 | 464 | 0.9920 | 0.6812 | 0.9920 | 0.9960 |
284
+ | No log | 4.1607 | 466 | 1.0414 | 0.6713 | 1.0414 | 1.0205 |
285
+ | No log | 4.1786 | 468 | 0.9863 | 0.6712 | 0.9863 | 0.9931 |
286
+ | No log | 4.1964 | 470 | 0.9939 | 0.6846 | 0.9939 | 0.9969 |
287
+ | No log | 4.2143 | 472 | 1.0790 | 0.6548 | 1.0790 | 1.0387 |
288
+ | No log | 4.2321 | 474 | 1.0321 | 0.6585 | 1.0321 | 1.0159 |
289
+ | No log | 4.25 | 476 | 0.9181 | 0.7152 | 0.9181 | 0.9582 |
290
+ | No log | 4.2679 | 478 | 0.8282 | 0.72 | 0.8282 | 0.9101 |
291
+ | No log | 4.2857 | 480 | 0.7953 | 0.7355 | 0.7953 | 0.8918 |
292
+ | No log | 4.3036 | 482 | 0.8073 | 0.7453 | 0.8073 | 0.8985 |
293
+ | No log | 4.3214 | 484 | 0.8607 | 0.7314 | 0.8607 | 0.9277 |
294
+ | No log | 4.3393 | 486 | 0.9328 | 0.6854 | 0.9328 | 0.9658 |
295
+ | No log | 4.3571 | 488 | 1.0499 | 0.6816 | 1.0499 | 1.0247 |
296
+ | No log | 4.375 | 490 | 0.8771 | 0.7143 | 0.8771 | 0.9366 |
297
+ | No log | 4.3929 | 492 | 0.7285 | 0.7296 | 0.7285 | 0.8535 |
298
+ | No log | 4.4107 | 494 | 0.6230 | 0.76 | 0.6230 | 0.7893 |
299
+ | No log | 4.4286 | 496 | 0.5915 | 0.7733 | 0.5915 | 0.7691 |
300
+ | No log | 4.4464 | 498 | 0.6233 | 0.7712 | 0.6233 | 0.7895 |
301
+ | 0.4386 | 4.4643 | 500 | 0.8193 | 0.7412 | 0.8193 | 0.9051 |
302
+ | 0.4386 | 4.4821 | 502 | 1.1280 | 0.6907 | 1.1280 | 1.0621 |
303
+ | 0.4386 | 4.5 | 504 | 1.2010 | 0.6528 | 1.2010 | 1.0959 |
304
+ | 0.4386 | 4.5179 | 506 | 1.0706 | 0.6971 | 1.0706 | 1.0347 |
305
+ | 0.4386 | 4.5357 | 508 | 0.8758 | 0.6875 | 0.8758 | 0.9359 |
306
+ | 0.4386 | 4.5536 | 510 | 0.8033 | 0.7105 | 0.8033 | 0.8963 |
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 sha256:53684ea363f6e2b80955a2efb69ed58e2fc63cccc6d61977318234c04e3adf5c
3
+ size 540799996
training_args.bin ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:b4be6d8de02e8e6f94ce24aa0ed9cfeb3c413b259cb7addf300b1262f18d3341
3
+ size 5304