Hugging Face's logo

AllanK24
/
mask2former-swin-large-apple-dms-run5

Image Segmentation
Transformers
TensorBoard
Safetensors
mask2former
vision
material-segmentation
Generated from Trainer
Model card Files
xet
 Metrics Community

mask2former-swin-large-apple-dms-run5

This model is a fine-tuned version of facebook/mask2former-swin-large-ade-semantic on the AllanK24/apple-dms-materials dataset. It achieves the following results on the evaluation set:

  • Mean Iou: 0.4092
  • Mean Accuracy: 0.4515
  • Overall Accuracy: 0.7668
  • Iou Animal Skin: 0.1578
  • Accuracy Animal Skin: 0.1806
  • Iou Bone Teeth Horn: 0.0798
  • Accuracy Bone Teeth Horn: 0.0820
  • Iou Brickwork: 0.6137
  • Accuracy Brickwork: 0.6665
  • Iou Cardboard: 0.5351
  • Accuracy Cardboard: 0.5757
  • Iou Carpet Rug: 0.7736
  • Accuracy Carpet Rug: 0.8370
  • Iou Ceiling Tile: 0.7898
  • Accuracy Ceiling Tile: 0.8378
  • Iou Ceramic: 0.7090
  • Accuracy Ceramic: 0.7849
  • Iou Chalkboard Blackboard: 0.6888
  • Accuracy Chalkboard Blackboard: 0.7112
  • Iou Clutter: 0.0
  • Accuracy Clutter: 0.0
  • Iou Concrete: 0.2113
  • Accuracy Concrete: 0.2368
  • Iou Cork Corkboard: 0.0
  • Accuracy Cork Corkboard: 0.0
  • Iou Engineered Stone: 0.0
  • Accuracy Engineered Stone: 0.0
  • Iou Fabric Cloth: 0.8276
  • Accuracy Fabric Cloth: 0.8849
  • Iou Fiberglass Wool: 0.0
  • Accuracy Fiberglass Wool: 0.0
  • Iou Fire: 0.0577
  • Accuracy Fire: 0.0579
  • Iou Foliage: 0.8600
  • Accuracy Foliage: 0.9181
  • Iou Food: 0.8337
  • Accuracy Food: 0.9197
  • Iou Fur: 0.8343
  • Accuracy Fur: 0.9423
  • Iou Gemstone Quartz: 0.0
  • Accuracy Gemstone Quartz: 0.0
  • Iou Glass: 0.6482
  • Accuracy Glass: 0.7210
  • Iou Hair: 0.7722
  • Accuracy Hair: 0.8626
  • Iou Ice: 0.0
  • Accuracy Ice: 0.0
  • Iou Leather: 0.4223
  • Accuracy Leather: 0.4549
  • Iou Liquid Non-water: 0.0
  • Accuracy Liquid Non-water: 0.0
  • Iou Metal: 0.3931
  • Accuracy Metal: 0.4598
  • Iou Mirror: 0.6222
  • Accuracy Mirror: 0.6854
  • Iou Paint Plaster Enamel: 0.7474
  • Accuracy Paint Plaster Enamel: 0.8087
  • Iou Paper: 0.6602
  • Accuracy Paper: 0.7341
  • Iou Pearl: 0.0
  • Accuracy Pearl: 0.0
  • Iou Photograph Painting: 0.2659
  • Accuracy Photograph Painting: 0.2848
  • Iou Plastic Clear: 0.2922
  • Accuracy Plastic Clear: 0.3171
  • Iou Plastic Non-clear: 0.3641
  • Accuracy Plastic Non-clear: 0.4142
  • Iou Rubber Latex: 0.2416
  • Accuracy Rubber Latex: 0.2620
  • Iou Sand: 0.0
  • Accuracy Sand: 0.0
  • Iou Skin Lips: 0.7869
  • Accuracy Skin Lips: 0.8730
  • Iou Sky: 0.9294
  • Accuracy Sky: 0.9489
  • Iou Snow: 0.3728
  • Accuracy Snow: 0.3952
  • Iou Soap: 0.0
  • Accuracy Soap: 0.0
  • Iou Soil Mud: 0.3733
  • Accuracy Soil Mud: 0.6259
  • Iou Sponge: 0.0
  • Accuracy Sponge: 0.0
  • Iou Stone Natural: 0.5063
  • Accuracy Stone Natural: 0.5774
  • Iou Stone Polished: 0.0582
  • Accuracy Stone Polished: 0.0584
  • Iou Styrofoam: 0.0
  • Accuracy Styrofoam: 0.0
  • Iou Tile: 0.6665
  • Accuracy Tile: 0.7335
  • Iou Wallpaper: 0.4923
  • Accuracy Wallpaper: 0.5730
  • Iou Water: 0.8294
  • Accuracy Water: 0.9135
  • Iou Wax: 0.1683
  • Accuracy Wax: 0.1785
  • Iou Whiteboard: 0.7212
  • Accuracy Whiteboard: 0.7607
  • Iou Wicker: 0.3975
  • Accuracy Wicker: 0.4169
  • Iou Wood: 0.7545
  • Accuracy Wood: 0.8255
  • Iou Wood Tree: 0.4079
  • Accuracy Wood Tree: 0.4684
  • Iou Asphalt: 0.4139
  • Accuracy Asphalt: 0.4880
  • Loss: 240.7806
  • Eval Runtime: 35.2182
  • Eval Samples Per Second: 33.619
  • Eval Steps Per Second: 16.809

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:

  • learning_rate: 0.001
  • train_batch_size: 32
  • eval_batch_size: 16
  • seed: 42
  • distributed_type: multi-GPU
  • num_devices: 8
  • total_train_batch_size: 256
  • total_eval_batch_size: 128
  • optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • lr_scheduler_type: cosine
  • lr_scheduler_warmup_steps: 0.1
  • num_epochs: 20

Training results

Training Loss Epoch Step Mean Iou Mean Accuracy Overall Accuracy Iou Animal Skin Accuracy Animal Skin Iou Bone Teeth Horn Accuracy Bone Teeth Horn Iou Brickwork Accuracy Brickwork Iou Cardboard Accuracy Cardboard Iou Carpet Rug Accuracy Carpet Rug Iou Ceiling Tile Accuracy Ceiling Tile Iou Ceramic Accuracy Ceramic Iou Chalkboard Blackboard Accuracy Chalkboard Blackboard Iou Clutter Accuracy Clutter Iou Concrete Accuracy Concrete Iou Cork Corkboard Accuracy Cork Corkboard Iou Engineered Stone Accuracy Engineered Stone Iou Fabric Cloth Accuracy Fabric Cloth Iou Fiberglass Wool Accuracy Fiberglass Wool Iou Fire Accuracy Fire Iou Foliage Accuracy Foliage Iou Food Accuracy Food Iou Fur Accuracy Fur Iou Gemstone Quartz Accuracy Gemstone Quartz Iou Glass Accuracy Glass Iou Hair Accuracy Hair Iou Ice Accuracy Ice Iou Leather Accuracy Leather Iou Liquid Non-water Accuracy Liquid Non-water Iou Metal Accuracy Metal Iou Mirror Accuracy Mirror Iou Paint Plaster Enamel Accuracy Paint Plaster Enamel Iou Paper Accuracy Paper Iou Pearl Accuracy Pearl Iou Photograph Painting Accuracy Photograph Painting Iou Plastic Clear Accuracy Plastic Clear Iou Plastic Non-clear Accuracy Plastic Non-clear Iou Rubber Latex Accuracy Rubber Latex Iou Sand Accuracy Sand Iou Skin Lips Accuracy Skin Lips Iou Sky Accuracy Sky Iou Snow Accuracy Snow Iou Soap Accuracy Soap Iou Soil Mud Accuracy Soil Mud Iou Sponge Accuracy Sponge Iou Stone Natural Accuracy Stone Natural Iou Stone Polished Accuracy Stone Polished Iou Styrofoam Accuracy Styrofoam Iou Tile Accuracy Tile Iou Wallpaper Accuracy Wallpaper Iou Water Accuracy Water Iou Wax Accuracy Wax Iou Whiteboard Accuracy Whiteboard Iou Wicker Accuracy Wicker Iou Wood Accuracy Wood Iou Wood Tree Accuracy Wood Tree Iou Asphalt Accuracy Asphalt Validation Loss Eval Runtime Eval Samples Per Second Eval Steps Per Second
280.1148 1.7045 150 0.2157 0.2402 0.6236 0.0 0.0 0.0124 0.0125 0.2288 0.2549 0.0043 0.0043 0.3092 0.3173 0.7319 0.7978 0.2896 0.3020 0.1502 0.1502 0.0 0.0 0.0000 0.0000 0.0 0.0 0.0 0.0 0.7812 0.8493 0.0 0.0 0.0 0.0 0.7985 0.8420 0.5168 0.7449 0.2533 0.2651 0.0 0.0 0.5540 0.6777 0.7199 0.7991 0.0 0.0 0.0481 0.0507 0.0 0.0 0.1376 0.1439 0.4760 0.5132 0.6778 0.7475 0.5443 0.6549 0.0 0.0 0.0714 0.0743 0.1016 0.1283 0.1456 0.1534 0.0065 0.0066 0.0 0.0 0.7090 0.8397 0.9052 0.9277 0.0 0.0 0.0 0.0 0.0387 0.0423 0.0 0.0 0.0049 0.0049 0.0 0.0 0.0 0.0 0.3976 0.4167 0.0205 0.0206 0.7744 0.9122 0.0 0.0 0.0846 0.0854 0.1113 0.1131 0.5825 0.6110 0.0269 0.0274 0.0 0.0 281.0063 44.6722 26.504 13.252
280.1148 1.7045 150 0.2157 0.2402 0.6236 0.0 0.0 0.0124 0.0125 0.2288 0.2549 0.0043 0.0043 0.3092 0.3173 0.7319 0.7978 0.2896 0.3020 0.1502 0.1502 0.0 0.0 0.0000 0.0000 0.0 0.0 0.0 0.0 0.7812 0.8493 0.0 0.0 0.0 0.0 0.7985 0.8420 0.5168 0.7449 0.2533 0.2651 0.0 0.0 0.5540 0.6777 0.7199 0.7991 0.0 0.0 0.0481 0.0507 0.0 0.0 0.1376 0.1439 0.4760 0.5132 0.6778 0.7475 0.5443 0.6549 0.0 0.0 0.0714 0.0743 0.1016 0.1283 0.1456 0.1534 0.0065 0.0066 0.0 0.0 0.7090 0.8397 0.9052 0.9277 0.0 0.0 0.0 0.0 0.0387 0.0423 0.0 0.0 0.0049 0.0049 0.0 0.0 0.0 0.0 0.3976 0.4167 0.0205 0.0206 0.7744 0.9122 0.0 0.0 0.0846 0.0854 0.1113 0.1131 0.5825 0.6110 0.0269 0.0274 0.0 0.0 281.0063 44.6722 26.504 13.252
254.2010 3.4091 300 0.2997 0.3491 0.7301 0.0014 0.0014 0.0548 0.0565 0.3599 0.4315 0.3327 0.3502 0.7249 0.8270 0.7654 0.8239 0.6807 0.8165 0.2110 0.4577 0.0 0.0 0.0044 0.0044 0.0 0.0 0.0 0.0 0.7980 0.8780 0.0 0.0 0.0 0.0 0.8435 0.9263 0.5726 0.8751 0.6933 0.8087 0.0 0.0 0.5288 0.5760 0.7318 0.8667 0.0 0.0 0.4473 0.5399 0.0 0.0 0.3345 0.4019 0.4783 0.5437 0.7255 0.8132 0.5884 0.6737 0.0 0.0 0.0888 0.0913 0.0836 0.0858 0.2658 0.2894 0.1202 0.1233 0.0 0.0 0.7416 0.8210 0.9116 0.9292 0.0 0.0 0.0 0.0 0.2215 0.2618 0.0 0.0 0.2669 0.3613 0.0726 0.0734 0.0 0.0 0.5931 0.7034 0.0917 0.0941 0.7884 0.9096 0.0008 0.0008 0.4138 0.5365 0.3021 0.3093 0.7167 0.8612 0.0273 0.0276 0.0 0.0 270.0911 40.6048 29.159 14.58
254.2010 3.4091 300 0.2997 0.3491 0.7301 0.0014 0.0014 0.0548 0.0565 0.3599 0.4315 0.3327 0.3502 0.7249 0.8270 0.7654 0.8239 0.6807 0.8165 0.2110 0.4577 0.0 0.0 0.0044 0.0044 0.0 0.0 0.0 0.0 0.7980 0.8780 0.0 0.0 0.0 0.0 0.8435 0.9263 0.5726 0.8751 0.6933 0.8087 0.0 0.0 0.5288 0.5760 0.7318 0.8667 0.0 0.0 0.4473 0.5399 0.0 0.0 0.3345 0.4019 0.4783 0.5437 0.7255 0.8132 0.5884 0.6737 0.0 0.0 0.0888 0.0913 0.0836 0.0858 0.2658 0.2894 0.1202 0.1233 0.0 0.0 0.7416 0.8210 0.9116 0.9292 0.0 0.0 0.0 0.0 0.2215 0.2618 0.0 0.0 0.2669 0.3613 0.0726 0.0734 0.0 0.0 0.5931 0.7034 0.0917 0.0941 0.7884 0.9096 0.0008 0.0008 0.4138 0.5365 0.3021 0.3093 0.7167 0.8612 0.0273 0.0276 0.0 0.0 270.0911 40.6048 29.159 14.58
246.0082 5.1136 450 0.3094 0.3499 0.7156 0.0237 0.0365 0.0889 0.0964 0.2901 0.2955 0.4149 0.4293 0.6695 0.8088 0.7380 0.7716 0.5741 0.7981 0.3848 0.5694 0.0 0.0 0.0461 0.0502 0.0 0.0 0.0 0.0 0.8048 0.8828 0.0 0.0 0.0 0.0 0.8497 0.9220 0.7930 0.8783 0.7068 0.7625 0.0 0.0 0.6212 0.7257 0.7482 0.8172 0.0 0.0 0.3608 0.4002 0.0 0.0 0.3034 0.3402 0.5371 0.5949 0.7180 0.7937 0.6349 0.7202 0.0 0.0 0.1100 0.1129 0.1046 0.1066 0.2522 0.2710 0.2388 0.2630 0.0 0.0 0.7522 0.8376 0.9179 0.9343 0.0 0.0 0.0 0.0 0.3169 0.4554 0.0 0.0 0.3270 0.3710 0.0026 0.0026 0.0 0.0 0.5532 0.6249 0.0 0.0 0.8350 0.9261 0.0 0.0 0.2253 0.2261 0.2495 0.4248 0.6798 0.7247 0.1485 0.1531 0.0677 0.0694 262.0866 37.3966 31.661 15.83
246.0082 5.1136 450 0.3094 0.3499 0.7156 0.0237 0.0365 0.0889 0.0964 0.2901 0.2955 0.4149 0.4293 0.6695 0.8088 0.7380 0.7716 0.5741 0.7981 0.3848 0.5694 0.0 0.0 0.0461 0.0502 0.0 0.0 0.0 0.0 0.8048 0.8828 0.0 0.0 0.0 0.0 0.8497 0.9220 0.7930 0.8783 0.7068 0.7625 0.0 0.0 0.6212 0.7257 0.7482 0.8172 0.0 0.0 0.3608 0.4002 0.0 0.0 0.3034 0.3402 0.5371 0.5949 0.7180 0.7937 0.6349 0.7202 0.0 0.0 0.1100 0.1129 0.1046 0.1066 0.2522 0.2710 0.2388 0.2630 0.0 0.0 0.7522 0.8376 0.9179 0.9343 0.0 0.0 0.0 0.0 0.3169 0.4554 0.0 0.0 0.3270 0.3710 0.0026 0.0026 0.0 0.0 0.5532 0.6249 0.0 0.0 0.8350 0.9261 0.0 0.0 0.2253 0.2261 0.2495 0.4248 0.6798 0.7247 0.1485 0.1531 0.0677 0.0694 262.0866 37.3966 31.661 15.83
240.4236 6.8182 600 0.3133 0.3494 0.7104 0.0818 0.1591 0.0528 0.0538 0.5362 0.5712 0.3902 0.4089 0.6895 0.7503 0.7585 0.8159 0.5775 0.6182 0.3895 0.5143 0.0 0.0 0.0341 0.0347 0.0 0.0 0.0 0.0 0.8092 0.8781 0.0 0.0 0.0 0.0 0.8432 0.9213 0.7220 0.8729 0.6264 0.6597 0.0 0.0 0.6054 0.6723 0.7565 0.8352 0.0 0.0 0.1553 0.1608 0.0 0.0 0.3295 0.3721 0.5529 0.5944 0.6996 0.7465 0.6115 0.7005 0.0 0.0 0.2328 0.2485 0.1049 0.1159 0.3441 0.4034 0.1922 0.2023 0.0 0.0 0.7582 0.8537 0.9168 0.9388 0.0 0.0 0.0 0.0 0.2583 0.4114 0.0 0.0 0.3488 0.4054 0.0008 0.0008 0.0 0.0 0.6324 0.7508 0.2176 0.2242 0.8022 0.9089 0.0034 0.0034 0.0802 0.0804 0.1569 0.1830 0.7139 0.7735 0.1409 0.1441 0.1657 0.1805 259.9500 37.0094 31.992 15.996
240.4236 6.8182 600 0.3133 0.3494 0.7104 0.0818 0.1591 0.0528 0.0538 0.5362 0.5712 0.3902 0.4089 0.6895 0.7503 0.7585 0.8159 0.5775 0.6182 0.3895 0.5143 0.0 0.0 0.0341 0.0347 0.0 0.0 0.0 0.0 0.8092 0.8781 0.0 0.0 0.0 0.0 0.8432 0.9213 0.7220 0.8729 0.6264 0.6597 0.0 0.0 0.6054 0.6723 0.7565 0.8352 0.0 0.0 0.1553 0.1608 0.0 0.0 0.3295 0.3721 0.5529 0.5944 0.6996 0.7465 0.6115 0.7005 0.0 0.0 0.2328 0.2485 0.1049 0.1159 0.3441 0.4034 0.1922 0.2023 0.0 0.0 0.7582 0.8537 0.9168 0.9388 0.0 0.0 0.0 0.0 0.2583 0.4114 0.0 0.0 0.3488 0.4054 0.0008 0.0008 0.0 0.0 0.6324 0.7508 0.2176 0.2242 0.8022 0.9089 0.0034 0.0034 0.0802 0.0804 0.1569 0.1830 0.7139 0.7735 0.1409 0.1441 0.1657 0.1805 259.9500 37.0094 31.992 15.996
236.5460 8.5227 750 0.3604 0.4044 0.7537 0.1151 0.1615 0.0730 0.0763 0.5533 0.6144 0.4992 0.5731 0.6880 0.7299 0.7898 0.8616 0.6955 0.8357 0.4840 0.4933 0.0 0.0 0.0479 0.0489 0.0 0.0 0.0 0.0 0.7923 0.8931 0.0 0.0 0.0 0.0 0.8481 0.9453 0.7641 0.9175 0.7866 0.8759 0.0 0.0 0.6320 0.7240 0.7579 0.8538 0.0 0.0 0.4788 0.5277 0.0 0.0 0.3617 0.4299 0.5647 0.6182 0.7518 0.8328 0.5948 0.6588 0.0 0.0 0.1969 0.2045 0.1855 0.2233 0.3513 0.4063 0.1897 0.2012 0.0058 0.0059 0.7691 0.8589 0.9226 0.9485 0.0081 0.0081 0.0 0.0 0.2095 0.2349 0.0 0.0 0.3613 0.4080 0.0300 0.0300 0.0 0.0 0.6523 0.7504 0.4385 0.5011 0.8232 0.9119 0.0627 0.0642 0.5927 0.7055 0.4648 0.4888 0.7111 0.7569 0.2917 0.3403 0.1963 0.3091 255.3072 38.2949 30.918 15.459
236.5460 8.5227 750 0.3604 0.4044 0.7537 0.1151 0.1615 0.0730 0.0763 0.5533 0.6144 0.4992 0.5731 0.6880 0.7299 0.7898 0.8616 0.6955 0.8357 0.4840 0.4933 0.0 0.0 0.0479 0.0489 0.0 0.0 0.0 0.0 0.7923 0.8931 0.0 0.0 0.0 0.0 0.8481 0.9453 0.7641 0.9175 0.7866 0.8759 0.0 0.0 0.6320 0.7240 0.7579 0.8538 0.0 0.0 0.4788 0.5277 0.0 0.0 0.3617 0.4299 0.5647 0.6182 0.7518 0.8328 0.5948 0.6588 0.0 0.0 0.1969 0.2045 0.1855 0.2233 0.3513 0.4063 0.1897 0.2012 0.0058 0.0059 0.7691 0.8589 0.9226 0.9485 0.0081 0.0081 0.0 0.0 0.2095 0.2349 0.0 0.0 0.3613 0.4080 0.0300 0.0300 0.0 0.0 0.6523 0.7504 0.4385 0.5011 0.8232 0.9119 0.0627 0.0642 0.5927 0.7055 0.4648 0.4888 0.7111 0.7569 0.2917 0.3403 0.1963 0.3091 255.3072 38.2949 30.918 15.459
230.3069 10.2273 900 0.2936 0.3117 0.6713 0.0106 0.0107 0.0589 0.0602 0.2291 0.2310 0.4234 0.4420 0.5590 0.5745 0.7459 0.8027 0.5748 0.6008 0.3065 0.3077 0.0 0.0 0.0345 0.0354 0.0 0.0 0.0 0.0 0.8024 0.8436 0.0 0.0 0.0132 0.0136 0.8384 0.8892 0.5313 0.5447 0.4141 0.4277 0.0 0.0 0.5956 0.6523 0.7574 0.8365 0.0 0.0 0.0746 0.0748 0.0 0.0 0.2863 0.3161 0.5896 0.6369 0.7082 0.7516 0.5373 0.5619 0.0 0.0 0.2363 0.2500 0.0994 0.1022 0.2309 0.2424 0.1760 0.1820 0.0 0.0 0.7725 0.8611 0.9102 0.9235 0.0385 0.0385 0.0 0.0 0.1432 0.1675 0.0 0.0 0.2567 0.2744 0.0 0.0 0.0 0.0 0.5177 0.5364 0.3242 0.3587 0.8256 0.8928 0.0486 0.0489 0.4781 0.5078 0.1178 0.1187 0.7125 0.7700 0.2805 0.3134 0.0051 0.0051 253.4623 39.0006 30.359 15.179
230.3069 10.2273 900 0.2936 0.3117 0.6713 0.0106 0.0107 0.0589 0.0602 0.2291 0.2310 0.4234 0.4420 0.5590 0.5745 0.7459 0.8027 0.5748 0.6008 0.3065 0.3077 0.0 0.0 0.0345 0.0354 0.0 0.0 0.0 0.0 0.8024 0.8436 0.0 0.0 0.0132 0.0136 0.8384 0.8892 0.5313 0.5447 0.4141 0.4277 0.0 0.0 0.5956 0.6523 0.7574 0.8365 0.0 0.0 0.0746 0.0748 0.0 0.0 0.2863 0.3161 0.5896 0.6369 0.7082 0.7516 0.5373 0.5619 0.0 0.0 0.2363 0.2500 0.0994 0.1022 0.2309 0.2424 0.1760 0.1820 0.0 0.0 0.7725 0.8611 0.9102 0.9235 0.0385 0.0385 0.0 0.0 0.1432 0.1675 0.0 0.0 0.2567 0.2744 0.0 0.0 0.0 0.0 0.5177 0.5364 0.3242 0.3587 0.8256 0.8928 0.0486 0.0489 0.4781 0.5078 0.1178 0.1187 0.7125 0.7700 0.2805 0.3134 0.0051 0.0051 253.4623 39.0006 30.359 15.179
226.3873 11.9318 1050 0.3760 0.4151 0.7488 0.0293 0.0297 0.0635 0.0651 0.5553 0.6489 0.5000 0.5199 0.7576 0.8431 0.7793 0.8336 0.6875 0.7593 0.6576 0.6775 0.0 0.0 0.0436 0.0451 0.0 0.0 0.0 0.0 0.8203 0.8956 0.0 0.0 0.0064 0.0065 0.8511 0.9239 0.7868 0.8587 0.7817 0.8857 0.0 0.0 0.6171 0.6795 0.7647 0.8705 0.0 0.0 0.3051 0.3202 0.0 0.0 0.3953 0.4613 0.6016 0.6927 0.7390 0.7959 0.6352 0.7132 0.0 0.0 0.3039 0.3375 0.2249 0.2427 0.3492 0.3947 0.2028 0.2140 0.0200 0.0200 0.7766 0.8814 0.9262 0.9469 0.2893 0.2898 0.0 0.0 0.3581 0.4667 0.0 0.0 0.4221 0.4987 0.0171 0.0171 0.0 0.0 0.6035 0.6579 0.4544 0.5174 0.8227 0.9081 0.0398 0.0400 0.6760 0.7096 0.3046 0.3172 0.7505 0.8217 0.2830 0.3014 0.3510 0.4776 249.7391 38.6894 30.603 15.301
226.3873 11.9318 1050 0.3760 0.4151 0.7488 0.0293 0.0297 0.0635 0.0651 0.5553 0.6489 0.5000 0.5199 0.7576 0.8431 0.7793 0.8336 0.6875 0.7593 0.6576 0.6775 0.0 0.0 0.0436 0.0451 0.0 0.0 0.0 0.0 0.8203 0.8956 0.0 0.0 0.0064 0.0065 0.8511 0.9239 0.7868 0.8587 0.7817 0.8857 0.0 0.0 0.6171 0.6795 0.7647 0.8705 0.0 0.0 0.3051 0.3202 0.0 0.0 0.3953 0.4613 0.6016 0.6927 0.7390 0.7959 0.6352 0.7132 0.0 0.0 0.3039 0.3375 0.2249 0.2427 0.3492 0.3947 0.2028 0.2140 0.0200 0.0200 0.7766 0.8814 0.9262 0.9469 0.2893 0.2898 0.0 0.0 0.3581 0.4667 0.0 0.0 0.4221 0.4987 0.0171 0.0171 0.0 0.0 0.6035 0.6579 0.4544 0.5174 0.8227 0.9081 0.0398 0.0400 0.6760 0.7096 0.3046 0.3172 0.7505 0.8217 0.2830 0.3014 0.3510 0.4776 249.7391 38.6894 30.603 15.301
221.8042 13.6364 1200 0.4016 0.4452 0.7686 0.0414 0.0473 0.0925 0.0971 0.6040 0.6446 0.5340 0.5727 0.7647 0.8497 0.7831 0.8674 0.7142 0.7892 0.6418 0.6652 0.0 0.0 0.2877 0.3611 0.0 0.0 0.0 0.0 0.8264 0.8918 0.0 0.0 0.0526 0.0527 0.8558 0.9191 0.8235 0.9118 0.8265 0.9445 0.0 0.0 0.6505 0.7393 0.7664 0.8502 0.0 0.0 0.4512 0.4857 0.0 0.0 0.4085 0.4970 0.5738 0.6082 0.7424 0.7998 0.6561 0.7482 0.0 0.0 0.2501 0.2726 0.2858 0.3170 0.3866 0.4504 0.2421 0.2659 0.0 0.0 0.7782 0.8654 0.9304 0.9502 0.4416 0.4832 0.0 0.0 0.3602 0.5646 0.0 0.0 0.4479 0.5174 0.0845 0.0850 0.0 0.0 0.6760 0.7633 0.4610 0.5202 0.8280 0.9242 0.0712 0.0731 0.6490 0.6763 0.4068 0.4222 0.7522 0.8143 0.4115 0.4827 0.3258 0.3620 245.4609 36.4566 32.477 16.238
221.8042 13.6364 1200 0.4016 0.4452 0.7686 0.0414 0.0473 0.0925 0.0971 0.6040 0.6446 0.5340 0.5727 0.7647 0.8497 0.7831 0.8674 0.7142 0.7892 0.6418 0.6652 0.0 0.0 0.2877 0.3611 0.0 0.0 0.0 0.0 0.8264 0.8918 0.0 0.0 0.0526 0.0527 0.8558 0.9191 0.8235 0.9118 0.8265 0.9445 0.0 0.0 0.6505 0.7393 0.7664 0.8502 0.0 0.0 0.4512 0.4857 0.0 0.0 0.4085 0.4970 0.5738 0.6082 0.7424 0.7998 0.6561 0.7482 0.0 0.0 0.2501 0.2726 0.2858 0.3170 0.3866 0.4504 0.2421 0.2659 0.0 0.0 0.7782 0.8654 0.9304 0.9502 0.4416 0.4832 0.0 0.0 0.3602 0.5646 0.0 0.0 0.4479 0.5174 0.0845 0.0850 0.0 0.0 0.6760 0.7633 0.4610 0.5202 0.8280 0.9242 0.0712 0.0731 0.6490 0.6763 0.4068 0.4222 0.7522 0.8143 0.4115 0.4827 0.3258 0.3620 245.4609 36.4566 32.477 16.238
218.4526 15.3409 1350 0.4062 0.4476 0.7564 0.2279 0.2550 0.0922 0.0971 0.6175 0.6688 0.4974 0.5354 0.7729 0.8433 0.7603 0.7949 0.7176 0.8029 0.6590 0.6821 0.0 0.0 0.1481 0.1624 0.0 0.0 0.0 0.0 0.8282 0.8882 0.0 0.0 0.0221 0.0222 0.8563 0.9214 0.8086 0.9268 0.8333 0.9315 0.0 0.0 0.6486 0.7346 0.7689 0.8537 0.0 0.0 0.4817 0.5283 0.0 0.0 0.3704 0.4269 0.6339 0.7093 0.7392 0.7930 0.6567 0.7430 0.0 0.0 0.2088 0.2174 0.2482 0.2668 0.3493 0.3897 0.2311 0.2515 0.0 0.0 0.7848 0.8737 0.9233 0.9394 0.5041 0.5268 0.0 0.0 0.3841 0.6280 0.0 0.0 0.4925 0.5649 0.0342 0.0343 0.0 0.0 0.6654 0.7461 0.5133 0.6033 0.8368 0.9157 0.1601 0.1648 0.6902 0.7050 0.4655 0.4871 0.7220 0.7768 0.3532 0.4006 0.4136 0.4634 243.2676 38.0117 31.148 15.574
218.4526 15.3409 1350 0.4062 0.4476 0.7564 0.2279 0.2550 0.0922 0.0971 0.6175 0.6688 0.4974 0.5354 0.7729 0.8433 0.7603 0.7949 0.7176 0.8029 0.6590 0.6821 0.0 0.0 0.1481 0.1624 0.0 0.0 0.0 0.0 0.8282 0.8882 0.0 0.0 0.0221 0.0222 0.8563 0.9214 0.8086 0.9268 0.8333 0.9315 0.0 0.0 0.6486 0.7346 0.7689 0.8537 0.0 0.0 0.4817 0.5283 0.0 0.0 0.3704 0.4269 0.6339 0.7093 0.7392 0.7930 0.6567 0.7430 0.0 0.0 0.2088 0.2174 0.2482 0.2668 0.3493 0.3897 0.2311 0.2515 0.0 0.0 0.7848 0.8737 0.9233 0.9394 0.5041 0.5268 0.0 0.0 0.3841 0.6280 0.0 0.0 0.4925 0.5649 0.0342 0.0343 0.0 0.0 0.6654 0.7461 0.5133 0.6033 0.8368 0.9157 0.1601 0.1648 0.6902 0.7050 0.4655 0.4871 0.7220 0.7768 0.3532 0.4006 0.4136 0.4634 243.2676 38.0117 31.148 15.574
216.0369 17.0455 1500 0.4114 0.4541 0.7670 0.1337 0.1536 0.0762 0.0782 0.6149 0.6631 0.5149 0.5556 0.7663 0.8267 0.7824 0.8235 0.7096 0.7888 0.6704 0.6921 0.0 0.0 0.1768 0.1911 0.0 0.0 0.0 0.0 0.8271 0.8890 0.0 0.0 0.0379 0.0379 0.8557 0.9163 0.8370 0.9208 0.8306 0.9419 0.0 0.0 0.6525 0.7340 0.7712 0.8650 0.0 0.0 0.4756 0.5222 0.0 0.0 0.3930 0.4637 0.6238 0.7100 0.7475 0.8076 0.6638 0.7353 0.0 0.0 0.2931 0.3195 0.2900 0.3176 0.3674 0.4183 0.2376 0.2592 0.0 0.0 0.7867 0.8744 0.9241 0.9409 0.4915 0.5119 0.0 0.0 0.3568 0.5768 0.0 0.0 0.5218 0.6026 0.0604 0.0606 0.0 0.0 0.6563 0.7113 0.5066 0.6155 0.8303 0.9143 0.1510 0.1580 0.7092 0.7487 0.4811 0.5081 0.7550 0.8225 0.3900 0.4493 0.4240 0.4885 242.1257 39.3239 30.109 15.054
216.0369 17.0455 1500 0.4114 0.4541 0.7670 0.1337 0.1536 0.0762 0.0782 0.6149 0.6631 0.5149 0.5556 0.7663 0.8267 0.7824 0.8235 0.7096 0.7888 0.6704 0.6921 0.0 0.0 0.1768 0.1911 0.0 0.0 0.0 0.0 0.8271 0.8890 0.0 0.0 0.0379 0.0379 0.8557 0.9163 0.8370 0.9208 0.8306 0.9419 0.0 0.0 0.6525 0.7340 0.7712 0.8650 0.0 0.0 0.4756 0.5222 0.0 0.0 0.3930 0.4637 0.6238 0.7100 0.7475 0.8076 0.6638 0.7353 0.0 0.0 0.2931 0.3195 0.2900 0.3176 0.3674 0.4183 0.2376 0.2592 0.0 0.0 0.7867 0.8744 0.9241 0.9409 0.4915 0.5119 0.0 0.0 0.3568 0.5768 0.0 0.0 0.5218 0.6026 0.0604 0.0606 0.0 0.0 0.6563 0.7113 0.5066 0.6155 0.8303 0.9143 0.1510 0.1580 0.7092 0.7487 0.4811 0.5081 0.7550 0.8225 0.3900 0.4493 0.4240 0.4885 242.1257 39.3239 30.109 15.054
214.3244 18.75 1650 0.4092 0.4515 0.7668 0.1578 0.1806 0.0798 0.0820 0.6137 0.6665 0.5351 0.5757 0.7736 0.8370 0.7898 0.8378 0.7090 0.7849 0.6888 0.7112 0.0 0.0 0.2113 0.2368 0.0 0.0 0.0 0.0 0.8276 0.8849 0.0 0.0 0.0577 0.0579 0.8600 0.9181 0.8337 0.9197 0.8343 0.9423 0.0 0.0 0.6482 0.7210 0.7722 0.8626 0.0 0.0 0.4223 0.4549 0.0 0.0 0.3931 0.4598 0.6222 0.6854 0.7474 0.8087 0.6602 0.7341 0.0 0.0 0.2659 0.2848 0.2922 0.3171 0.3641 0.4142 0.2416 0.2620 0.0 0.0 0.7869 0.8730 0.9294 0.9489 0.3728 0.3952 0.0 0.0 0.3733 0.6259 0.0 0.0 0.5063 0.5774 0.0582 0.0584 0.0 0.0 0.6665 0.7335 0.4923 0.5730 0.8294 0.9135 0.1683 0.1785 0.7212 0.7607 0.3975 0.4169 0.7545 0.8255 0.4079 0.4684 0.4139 0.4880 240.7806 35.2182 33.619 16.809
214.3244 18.75 1650 0.4092 0.4515 0.7668 0.1578 0.1806 0.0798 0.0820 0.6137 0.6665 0.5351 0.5757 0.7736 0.8370 0.7898 0.8378 0.7090 0.7849 0.6888 0.7112 0.0 0.0 0.2113 0.2368 0.0 0.0 0.0 0.0 0.8276 0.8849 0.0 0.0 0.0577 0.0579 0.8600 0.9181 0.8337 0.9197 0.8343 0.9423 0.0 0.0 0.6482 0.7210 0.7722 0.8626 0.0 0.0 0.4223 0.4549 0.0 0.0 0.3931 0.4598 0.6222 0.6854 0.7474 0.8087 0.6602 0.7341 0.0 0.0 0.2659 0.2848 0.2922 0.3171 0.3641 0.4142 0.2416 0.2620 0.0 0.0 0.7869 0.8730 0.9294 0.9489 0.3728 0.3952 0.0 0.0 0.3733 0.6259 0.0 0.0 0.5063 0.5774 0.0582 0.0584 0.0 0.0 0.6665 0.7335 0.4923 0.5730 0.8294 0.9135 0.1683 0.1785 0.7212 0.7607 0.3975 0.4169 0.7545 0.8255 0.4079 0.4684 0.4139 0.4880 240.7806 35.2182 33.619 16.809

Framework versions

  • Transformers 5.0.0
  • Pytorch 2.9.1+cu128
  • Datasets 4.5.0
  • Tokenizers 0.22.2
Downloads last month
13
Safetensors
Model size
0.2B params
Tensor type
I64
·
F32
·
Inference Providers NEW
Image Segmentation
This model isn't deployed by any Inference Provider. 🙋 Ask for provider support

Model tree for AllanK24/mask2former-swin-large-apple-dms-run5

Base model

facebook/mask2former-swin-large-ade-semantic
Finetuned
(9)
this model