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detr_finetuned_cppe5

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metadata 
library_name: transformers
license: apache-2.0
base_model: microsoft/conditional-detr-resnet-50
tags:
  - trackio
  - trackio:https://huggingface.co/spaces/mustoof/trackio
  - generated_from_trainer
model-index:
  - name: detr_finetuned_cppe5
    results: []

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detr_finetuned_cppe5

This model is a fine-tuned version of microsoft/conditional-detr-resnet-50 on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 1.1071
  • Map: 0.119
  • Map 50: 0.1821
  • Map 75: 0.136
  • Map Small: -1.0
  • Map Medium: 0.1842
  • Map Large: 0.1216
  • Mar 1: 0.2314
  • Mar 10: 0.6086
  • Mar 100: 0.6743
  • Mar Small: -1.0
  • Mar Medium: 0.56
  • Mar Large: 0.727
  • Map Coverall: 0.4874
  • Mar 100 Coverall: 0.7564
  • Map Face Shield: 0.0248
  • Mar 100 Face Shield: 0.575
  • Map Gloves: 0.0054
  • Mar 100 Gloves: 0.56
  • Map Goggles: 0.027
  • Mar 100 Goggles: 0.68
  • Map Mask: 0.0505
  • Mar 100 Mask: 0.8

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: 5e-05
  • train_batch_size: 8
  • eval_batch_size: 8
  • seed: 42
  • 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
  • num_epochs: 30

Training results

Training Loss Epoch Step Validation Loss Map Map 50 Map 75 Map Small Map Medium Map Large Mar 1 Mar 10 Mar 100 Mar Small Mar Medium Mar Large Map Coverall Mar 100 Coverall Map Face Shield Mar 100 Face Shield Map Gloves Mar 100 Gloves Map Goggles Mar 100 Goggles Map Mask Mar 100 Mask
No log 1.0 107 2.7611 0.0058 0.0136 0.0049 -1.0 0.016 0.0057 0.016 0.0482 0.0844 -1.0 0.125 0.0842 0.0289 0.4096 0.0 0.0125 0.0 0.0 0.0 0.0 0.0 0.0
No log 2.0 214 2.2915 0.0036 0.0078 0.0023 -1.0 0.0325 0.0034 0.0226 0.0449 0.087 -1.0 0.12 0.0854 0.0178 0.3351 0.0 0.0 0.0 0.0 0.0 0.0 0.0001 0.1
No log 3.0 321 1.7695 0.0143 0.0229 0.0177 -1.0 0.0578 0.0142 0.0421 0.083 0.1268 -1.0 0.19 0.1254 0.0713 0.634 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
No log 4.0 428 1.5482 0.0206 0.0343 0.0208 -1.0 0.0673 0.0224 0.0787 0.1221 0.1723 -1.0 0.19 0.1905 0.0847 0.7213 0.0 0.0 0.0 0.0 0.0184 0.14 0.0 0.0
8.1722 5.0 535 1.6674 0.0127 0.0223 0.0142 -1.0 0.1018 0.0101 0.0511 0.0885 0.1298 -1.0 0.155 0.1301 0.0635 0.6489 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
8.1722 6.0 642 1.4786 0.0242 0.0357 0.0272 -1.0 0.0635 0.0231 0.0657 0.1138 0.1445 -1.0 0.17 0.1449 0.1208 0.7223 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
8.1722 7.0 749 1.4341 0.0448 0.0671 0.0503 -1.0 0.0718 0.0443 0.0859 0.1678 0.1829 -1.0 0.175 0.2087 0.2228 0.7096 0.0002 0.025 0.001 0.18 0.0 0.0 0.0 0.0
8.1722 8.0 856 1.4775 0.0498 0.0824 0.0568 -1.0 0.1009 0.0481 0.1031 0.1506 0.1821 -1.0 0.2 0.2049 0.2468 0.7128 0.0002 0.0375 0.0005 0.08 0.0017 0.08 0.0 0.0
8.1722 9.0 963 1.3853 0.0627 0.1041 0.0708 -1.0 0.1217 0.0612 0.1123 0.2701 0.3004 -1.0 0.2775 0.3649 0.3074 0.6947 0.0026 0.2875 0.0019 0.2 0.0014 0.32 0.0 0.0
1.4178 10.0 1070 1.3820 0.0701 0.1267 0.0751 -1.0 0.1374 0.0686 0.117 0.2942 0.3127 -1.0 0.2875 0.3709 0.342 0.6883 0.0039 0.375 0.0029 0.2 0.0014 0.3 0.0 0.0
1.4178 11.0 1177 1.3366 0.0698 0.1208 0.0775 -1.0 0.124 0.0691 0.1075 0.4472 0.484 -1.0 0.3425 0.5427 0.3325 0.7351 0.0044 0.525 0.0031 0.22 0.002 0.24 0.0071 0.7
1.4178 12.0 1284 1.3058 0.0817 0.1354 0.0891 -1.0 0.1416 0.0813 0.2395 0.4439 0.4698 -1.0 0.3625 0.5161 0.3898 0.734 0.0065 0.375 0.0028 0.22 0.0025 0.42 0.0068 0.6
1.4178 13.0 1391 1.2480 0.0775 0.1292 0.0829 -1.0 0.1393 0.0771 0.1652 0.3109 0.3654 -1.0 0.3375 0.429 0.373 0.7319 0.0087 0.475 0.0032 0.18 0.0027 0.44 0.0 0.0
1.4178 14.0 1498 1.2472 0.0797 0.1382 0.0819 -1.0 0.1505 0.0789 0.1525 0.498 0.5423 -1.0 0.3975 0.609 0.3821 0.734 0.0078 0.5375 0.0027 0.3 0.0033 0.44 0.0024 0.7
1.1690 15.0 1605 1.2123 0.0849 0.1444 0.0808 -1.0 0.1522 0.0847 0.1422 0.5243 0.5655 -1.0 0.4475 0.6276 0.4026 0.7277 0.0057 0.5 0.0066 0.5 0.0047 0.4 0.0049 0.7
1.1690 16.0 1712 1.2066 0.0854 0.1443 0.0925 -1.0 0.1542 0.085 0.1481 0.4081 0.4502 -1.0 0.425 0.527 0.4085 0.7383 0.0093 0.5125 0.0057 0.5 0.0034 0.5 0.0 0.0
1.1690 17.0 1819 1.1714 0.0917 0.1473 0.1008 -1.0 0.1494 0.0922 0.2175 0.5282 0.5724 -1.0 0.3475 0.6707 0.433 0.7372 0.0101 0.525 0.0047 0.44 0.0053 0.46 0.0052 0.7
1.1690 18.0 1926 1.1608 0.0901 0.1484 0.0969 -1.0 0.1562 0.0903 0.1703 0.5521 0.6052 -1.0 0.42 0.6923 0.4276 0.7309 0.0064 0.575 0.0055 0.54 0.005 0.48 0.0061 0.7
1.0151 19.0 2033 1.1450 0.0951 0.1492 0.1036 -1.0 0.177 0.0959 0.3218 0.5073 0.6137 -1.0 0.4175 0.7028 0.442 0.7511 0.0099 0.5375 0.0059 0.52 0.007 0.46 0.0105 0.8
1.0151 20.0 2140 1.1344 0.0979 0.1543 0.1089 -1.0 0.1594 0.0996 0.341 0.5887 0.6667 -1.0 0.4675 0.7528 0.4476 0.7511 0.0162 0.5625 0.0079 0.6 0.0077 0.52 0.0102 0.9
1.0151 21.0 2247 1.1657 0.1037 0.1633 0.1141 -1.0 0.1682 0.1061 0.3075 0.5472 0.6255 -1.0 0.41 0.7134 0.4508 0.75 0.0168 0.5375 0.0103 0.56 0.0069 0.48 0.0338 0.8
1.0151 22.0 2354 1.1491 0.1081 0.1674 0.1197 -1.0 0.1782 0.1084 0.3143 0.5535 0.6441 -1.0 0.4275 0.739 0.4672 0.7457 0.0164 0.575 0.0061 0.58 0.0075 0.52 0.0434 0.8
1.0151 23.0 2461 1.1182 0.1158 0.1798 0.1327 -1.0 0.196 0.117 0.3346 0.6329 0.6785 -1.0 0.5225 0.7506 0.4786 0.7574 0.0295 0.575 0.0069 0.6 0.0133 0.66 0.0506 0.8
0.8994 24.0 2568 1.1254 0.1117 0.1729 0.1259 -1.0 0.1871 0.1131 0.3556 0.5712 0.6801 -1.0 0.5775 0.7294 0.4814 0.7532 0.0261 0.5875 0.007 0.6 0.0101 0.66 0.034 0.8
0.8994 25.0 2675 1.1163 0.1161 0.1794 0.1314 -1.0 0.1911 0.1178 0.3531 0.5695 0.637 -1.0 0.565 0.6903 0.4819 0.7574 0.0292 0.5875 0.0053 0.58 0.0214 0.66 0.0429 0.6
0.8994 26.0 2782 1.1205 0.118 0.1809 0.1349 -1.0 0.1959 0.1202 0.2354 0.6258 0.6771 -1.0 0.5775 0.7266 0.4827 0.7553 0.0231 0.55 0.0056 0.56 0.0281 0.72 0.0505 0.8
0.8994 27.0 2889 1.1166 0.118 0.1792 0.134 -1.0 0.1777 0.121 0.2436 0.6389 0.6855 -1.0 0.5675 0.7408 0.4904 0.7574 0.0257 0.55 0.006 0.6 0.0277 0.72 0.0406 0.8
0.8994 28.0 2996 1.1101 0.1192 0.1809 0.1354 -1.0 0.1929 0.1217 0.217 0.6088 0.672 -1.0 0.56 0.7239 0.492 0.7574 0.021 0.5625 0.0054 0.56 0.027 0.68 0.0505 0.8
0.8507 29.0 3103 1.1055 0.119 0.1821 0.136 -1.0 0.1841 0.1216 0.2314 0.6061 0.6747 -1.0 0.56 0.7275 0.4874 0.7585 0.0248 0.575 0.0054 0.56 0.027 0.68 0.0505 0.8
0.8507 30.0 3210 1.1071 0.119 0.1821 0.136 -1.0 0.1842 0.1216 0.2314 0.6086 0.6743 -1.0 0.56 0.727 0.4874 0.7564 0.0248 0.575 0.0054 0.56 0.027 0.68 0.0505 0.8

Framework versions

  • Transformers 5.0.0
  • Pytorch 2.10.0+cu128
  • Datasets 4.0.0
  • Tokenizers 0.22.2