generated_from_trainer

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testing_100_epoches

This model is a fine-tuned version of nvidia/mit-b2 on an unknown dataset. It achieves the following results on the evaluation set:

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

Training results

Training Loss Epoch Step Validation Loss Mean Iou Mean Accuracy Overall Accuracy Accuracy Bkg Accuracy Wht Iou Bkg Iou Wht
0.1707 1.0 180 0.0800 0.0 0.0 0.0 nan 0.0 0.0 0.0
0.0919 2.0 360 0.0798 0.0 0.0 0.0 nan 0.0 0.0 0.0
0.0874 3.0 540 0.0771 0.0 0.0 0.0 nan 0.0 0.0 0.0
0.0843 4.0 720 0.0786 0.0 0.0 0.0 nan 0.0 0.0 0.0
0.0808 5.0 900 0.0805 0.0014 0.0029 0.0029 nan 0.0029 0.0 0.0029
0.0775 6.0 1080 0.0796 0.0 0.0 0.0 nan 0.0 0.0 0.0
0.0712 7.0 1260 0.0906 0.0381 0.0762 0.0762 nan 0.0762 0.0 0.0762
0.0629 8.0 1440 0.0830 0.0055 0.0110 0.0110 nan 0.0110 0.0 0.0110
0.0547 9.0 1620 0.0911 0.0141 0.0281 0.0281 nan 0.0281 0.0 0.0281
0.0483 10.0 1800 0.1032 0.0097 0.0194 0.0194 nan 0.0194 0.0 0.0194
0.0443 11.0 1980 0.0924 0.0146 0.0292 0.0292 nan 0.0292 0.0 0.0292
0.0406 12.0 2160 0.0979 0.0069 0.0137 0.0137 nan 0.0137 0.0 0.0137
0.0369 13.0 2340 0.1030 0.0103 0.0206 0.0206 nan 0.0206 0.0 0.0206
0.0352 14.0 2520 0.0993 0.0065 0.0129 0.0129 nan 0.0129 0.0 0.0129
0.0341 15.0 2700 0.0978 0.0062 0.0125 0.0125 nan 0.0125 0.0 0.0125
0.0324 16.0 2880 0.1044 0.0151 0.0302 0.0302 nan 0.0302 0.0 0.0302
0.0307 17.0 3060 0.1014 0.0164 0.0328 0.0328 nan 0.0328 0.0 0.0328
0.03 18.0 3240 0.1043 0.0128 0.0257 0.0257 nan 0.0257 0.0 0.0257
0.0295 19.0 3420 0.1093 0.0083 0.0165 0.0165 nan 0.0165 0.0 0.0165
0.0273 20.0 3600 0.1136 0.0100 0.0201 0.0201 nan 0.0201 0.0 0.0201
0.0264 21.0 3780 0.1086 0.0154 0.0309 0.0309 nan 0.0309 0.0 0.0309
0.0261 22.0 3960 0.1107 0.0165 0.0330 0.0330 nan 0.0330 0.0 0.0330
0.0257 23.0 4140 0.1119 0.0137 0.0274 0.0274 nan 0.0274 0.0 0.0274
0.0248 24.0 4320 0.1140 0.0101 0.0201 0.0201 nan 0.0201 0.0 0.0201
0.0242 25.0 4500 0.1056 0.0168 0.0336 0.0336 nan 0.0336 0.0 0.0336
0.024 26.0 4680 0.1143 0.0100 0.0200 0.0200 nan 0.0200 0.0 0.0200
0.0234 27.0 4860 0.1155 0.0091 0.0181 0.0181 nan 0.0181 0.0 0.0181
0.0228 28.0 5040 0.1201 0.0073 0.0146 0.0146 nan 0.0146 0.0 0.0146
0.0226 29.0 5220 0.1192 0.0094 0.0188 0.0188 nan 0.0188 0.0 0.0188
0.0224 30.0 5400 0.1187 0.0118 0.0237 0.0237 nan 0.0237 0.0 0.0237
0.0218 31.0 5580 0.1227 0.0105 0.0209 0.0209 nan 0.0209 0.0 0.0209
0.0211 32.0 5760 0.1159 0.0155 0.0310 0.0310 nan 0.0310 0.0 0.0310
0.0208 33.0 5940 0.1224 0.0108 0.0215 0.0215 nan 0.0215 0.0 0.0215
0.0203 34.0 6120 0.1239 0.0123 0.0246 0.0246 nan 0.0246 0.0 0.0246
0.0197 35.0 6300 0.1285 0.0065 0.0130 0.0130 nan 0.0130 0.0 0.0130
0.02 36.0 6480 0.1293 0.0037 0.0075 0.0075 nan 0.0075 0.0 0.0075
0.0192 37.0 6660 0.1258 0.0059 0.0119 0.0119 nan 0.0119 0.0 0.0119
0.0193 38.0 6840 0.1234 0.0105 0.0210 0.0210 nan 0.0210 0.0 0.0210
0.0189 39.0 7020 0.1267 0.0080 0.0159 0.0159 nan 0.0159 0.0 0.0159
0.0181 40.0 7200 0.1308 0.0060 0.0120 0.0120 nan 0.0120 0.0 0.0120
0.0183 41.0 7380 0.1337 0.0056 0.0112 0.0112 nan 0.0112 0.0 0.0112
0.018 42.0 7560 0.1349 0.0071 0.0142 0.0142 nan 0.0142 0.0 0.0142
0.0178 43.0 7740 0.1332 0.0069 0.0139 0.0139 nan 0.0139 0.0 0.0139
0.0171 44.0 7920 0.1363 0.0066 0.0132 0.0132 nan 0.0132 0.0 0.0132
0.0176 45.0 8100 0.1352 0.0065 0.0131 0.0131 nan 0.0131 0.0 0.0131
0.0181 46.0 8280 0.1384 0.0064 0.0127 0.0127 nan 0.0127 0.0 0.0127
0.0173 47.0 8460 0.1419 0.0065 0.0129 0.0129 nan 0.0129 0.0 0.0129
0.0176 48.0 8640 0.1374 0.0081 0.0161 0.0161 nan 0.0161 0.0 0.0161
0.0173 49.0 8820 0.1383 0.0065 0.0130 0.0130 nan 0.0130 0.0 0.0130
0.0173 50.0 9000 0.1400 0.0066 0.0133 0.0133 nan 0.0133 0.0 0.0133

Framework versions