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rtdetr-v2-r50-cppe5-finetune-2

Object Detection
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Safetensors
rt_detr_v2
Generated from Trainer
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End of training

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  1. README.md +120 -0
  2. config.json +132 -0
  3. model.safetensors +3 -0
  4. preprocessor_config.json +35 -0
  5. runs/May30_04-30-26_1132af90d1c5/events.out.tfevents.1748579429.1132af90d1c5.1275.0 +3 -0
  6. runs/May30_04-30-26_1132af90d1c5/events.out.tfevents.1748584312.1132af90d1c5.1275.1 +3 -0
  7. training_args.bin +3 -0
README.md ADDED
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+ ---
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+ library_name: transformers
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+ license: apache-2.0
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+ base_model: PekingU/rtdetr_v2_r50vd
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+ tags:
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+ - generated_from_trainer
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+ model-index:
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+ - name: rtdetr-v2-r50-cppe5-finetune-2
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+ results: []
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+ ---
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+
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+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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+ should probably proofread and complete it, then remove this comment. -->
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+
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+ # rtdetr-v2-r50-cppe5-finetune-2
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+
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+ This model is a fine-tuned version of [PekingU/rtdetr_v2_r50vd](https://huggingface.co/PekingU/rtdetr_v2_r50vd) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 9.6769
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+ - Map: 0.5368
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+ - Map 50: 0.8312
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+ - Map 75: 0.5962
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+ - Map Small: 0.5364
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+ - Map Medium: 0.441
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+ - Map Large: 0.7689
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+ - Mar 1: 0.3954
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+ - Mar 10: 0.6567
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+ - Mar 100: 0.6967
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+ - Mar Small: 0.6067
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+ - Mar Medium: 0.6153
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+ - Mar Large: 0.8557
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+ - Map Coverall: 0.5756
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+ - Mar 100 Coverall: 0.7821
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+ - Map Face Shield: 0.6521
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+ - Mar 100 Face Shield: 0.8059
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+ - Map Gloves: 0.4261
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+ - Mar 100 Gloves: 0.5627
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+ - Map Goggles: 0.4722
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+ - Mar 100 Goggles: 0.6897
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+ - Map Mask: 0.5578
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+ - Mar 100 Mask: 0.6431
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 5e-05
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+ - train_batch_size: 8
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+ - eval_batch_size: 8
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+ - seed: 42
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+ - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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+ - lr_scheduler_type: linear
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+ - lr_scheduler_warmup_steps: 300
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+ - num_epochs: 40
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+
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+ ### Training results
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+
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+ | 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 |
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+ |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:----------:|:---------:|:------:|:------:|:-------:|:---------:|:----------:|:---------:|:------------:|:----------------:|:---------------:|:-------------------:|:----------:|:--------------:|:-----------:|:---------------:|:--------:|:------------:|
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+ | No log | 1.0 | 107 | 25.4682 | 0.0465 | 0.0795 | 0.0437 | 0.0028 | 0.0102 | 0.0671 | 0.0688 | 0.1912 | 0.2765 | 0.1031 | 0.1968 | 0.5097 | 0.2085 | 0.5748 | 0.002 | 0.243 | 0.0029 | 0.1746 | 0.001 | 0.1492 | 0.0184 | 0.2409 |
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+ | No log | 2.0 | 214 | 15.4462 | 0.1823 | 0.3465 | 0.1617 | 0.0681 | 0.1115 | 0.2591 | 0.2151 | 0.4239 | 0.4884 | 0.2985 | 0.4232 | 0.7013 | 0.4591 | 0.6716 | 0.0879 | 0.5013 | 0.0658 | 0.3906 | 0.0495 | 0.4308 | 0.2489 | 0.4476 |
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+ | No log | 3.0 | 321 | 12.7644 | 0.2555 | 0.4657 | 0.2476 | 0.0847 | 0.191 | 0.4466 | 0.2627 | 0.4528 | 0.5148 | 0.2473 | 0.4805 | 0.7435 | 0.5487 | 0.7185 | 0.1397 | 0.5468 | 0.1609 | 0.4183 | 0.1243 | 0.4138 | 0.3041 | 0.4764 |
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+ | No log | 4.0 | 428 | 12.1356 | 0.2919 | 0.5558 | 0.2588 | 0.1466 | 0.2271 | 0.5099 | 0.285 | 0.4706 | 0.5293 | 0.3241 | 0.4886 | 0.729 | 0.5238 | 0.6986 | 0.2541 | 0.6101 | 0.1794 | 0.4281 | 0.1888 | 0.4508 | 0.3136 | 0.4587 |
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+ | 36.0648 | 5.0 | 535 | 11.8591 | 0.3218 | 0.5856 | 0.2997 | 0.1436 | 0.2566 | 0.5379 | 0.3028 | 0.4821 | 0.5359 | 0.3055 | 0.5098 | 0.7267 | 0.5498 | 0.7104 | 0.2962 | 0.6139 | 0.1811 | 0.4147 | 0.2364 | 0.46 | 0.3456 | 0.4804 |
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+ | 36.0648 | 6.0 | 642 | 11.7190 | 0.3157 | 0.5685 | 0.2997 | 0.1426 | 0.2557 | 0.5212 | 0.2823 | 0.4795 | 0.5398 | 0.3338 | 0.4924 | 0.7223 | 0.5437 | 0.7099 | 0.2111 | 0.5886 | 0.2288 | 0.4482 | 0.255 | 0.4677 | 0.34 | 0.4844 |
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+ | 36.0648 | 7.0 | 749 | 11.9062 | 0.3212 | 0.5979 | 0.2974 | 0.1367 | 0.259 | 0.5387 | 0.2942 | 0.4765 | 0.5428 | 0.3495 | 0.5085 | 0.7153 | 0.5386 | 0.6905 | 0.303 | 0.6139 | 0.2067 | 0.4522 | 0.209 | 0.4754 | 0.3487 | 0.4818 |
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+ | 36.0648 | 8.0 | 856 | 11.6933 | 0.3183 | 0.5969 | 0.2901 | 0.1414 | 0.2541 | 0.54 | 0.2977 | 0.483 | 0.5404 | 0.3387 | 0.4954 | 0.7399 | 0.5594 | 0.705 | 0.2812 | 0.6 | 0.2174 | 0.4429 | 0.208 | 0.4785 | 0.3253 | 0.4756 |
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+ | 36.0648 | 9.0 | 963 | 11.6233 | 0.3202 | 0.5826 | 0.3226 | 0.1359 | 0.2583 | 0.5543 | 0.3035 | 0.4884 | 0.5462 | 0.3383 | 0.5126 | 0.7321 | 0.5472 | 0.6937 | 0.2746 | 0.619 | 0.2086 | 0.4545 | 0.2237 | 0.4754 | 0.347 | 0.4884 |
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+ | 15.3215 | 10.0 | 1070 | 11.4090 | 0.3421 | 0.6207 | 0.3279 | 0.1389 | 0.2796 | 0.5757 | 0.316 | 0.4935 | 0.5477 | 0.3142 | 0.5067 | 0.745 | 0.5714 | 0.6991 | 0.3224 | 0.6278 | 0.2331 | 0.4371 | 0.2325 | 0.4754 | 0.3511 | 0.4991 |
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+ | 15.3215 | 11.0 | 1177 | 11.5408 | 0.3436 | 0.6394 | 0.3212 | 0.1544 | 0.2759 | 0.5751 | 0.3175 | 0.5003 | 0.5554 | 0.3501 | 0.5119 | 0.7464 | 0.5444 | 0.7059 | 0.329 | 0.5949 | 0.2259 | 0.4571 | 0.2647 | 0.5108 | 0.354 | 0.5084 |
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+ | 15.3215 | 12.0 | 1284 | 11.7707 | 0.3296 | 0.6169 | 0.3078 | 0.1525 | 0.2669 | 0.5336 | 0.3037 | 0.4793 | 0.5399 | 0.3164 | 0.4945 | 0.7323 | 0.5477 | 0.6892 | 0.32 | 0.6101 | 0.2295 | 0.429 | 0.21 | 0.4862 | 0.3408 | 0.4849 |
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+ | 15.3215 | 13.0 | 1391 | 11.6683 | 0.3415 | 0.6231 | 0.3243 | 0.1447 | 0.2795 | 0.5746 | 0.3181 | 0.4946 | 0.5536 | 0.3625 | 0.5028 | 0.7387 | 0.5571 | 0.6901 | 0.3245 | 0.6114 | 0.2424 | 0.4585 | 0.2356 | 0.5092 | 0.3479 | 0.4987 |
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+ | 15.3215 | 14.0 | 1498 | 11.7344 | 0.3305 | 0.6156 | 0.3133 | 0.1478 | 0.2877 | 0.5388 | 0.3194 | 0.4876 | 0.5468 | 0.3387 | 0.5232 | 0.7116 | 0.5236 | 0.7113 | 0.327 | 0.6 | 0.2255 | 0.4563 | 0.2373 | 0.4738 | 0.3391 | 0.4924 |
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+ | 13.4858 | 15.0 | 1605 | 11.6264 | 0.3307 | 0.6056 | 0.3161 | 0.1213 | 0.2799 | 0.5711 | 0.3242 | 0.4933 | 0.5506 | 0.3454 | 0.5066 | 0.7434 | 0.5581 | 0.7144 | 0.3034 | 0.5962 | 0.2163 | 0.4701 | 0.2598 | 0.4862 | 0.3159 | 0.4862 |
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+ | 13.4858 | 16.0 | 1712 | 11.5521 | 0.3287 | 0.6044 | 0.3125 | 0.1686 | 0.2751 | 0.5519 | 0.3171 | 0.4922 | 0.5484 | 0.3757 | 0.4978 | 0.7246 | 0.5635 | 0.7162 | 0.3018 | 0.5861 | 0.234 | 0.4714 | 0.236 | 0.48 | 0.3084 | 0.4884 |
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+ | 13.4858 | 17.0 | 1819 | 11.7578 | 0.3382 | 0.6292 | 0.3237 | 0.164 | 0.281 | 0.5516 | 0.3215 | 0.4924 | 0.548 | 0.3353 | 0.5037 | 0.7302 | 0.5505 | 0.709 | 0.3225 | 0.6076 | 0.2187 | 0.4402 | 0.2704 | 0.5031 | 0.3286 | 0.48 |
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+ | 13.4858 | 18.0 | 1926 | 11.5963 | 0.3454 | 0.6381 | 0.3218 | 0.1607 | 0.2921 | 0.5647 | 0.3294 | 0.4951 | 0.5507 | 0.3516 | 0.489 | 0.7565 | 0.5498 | 0.705 | 0.348 | 0.6051 | 0.2177 | 0.45 | 0.2613 | 0.5138 | 0.3504 | 0.4796 |
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+ | 12.4151 | 19.0 | 2033 | 11.5293 | 0.3469 | 0.6347 | 0.3237 | 0.1415 | 0.2967 | 0.5694 | 0.323 | 0.4923 | 0.5415 | 0.3126 | 0.4894 | 0.733 | 0.5663 | 0.7032 | 0.345 | 0.5975 | 0.2389 | 0.4469 | 0.2667 | 0.4846 | 0.3175 | 0.4756 |
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+ | 12.4151 | 20.0 | 2140 | 11.5551 | 0.3414 | 0.6306 | 0.3143 | 0.1716 | 0.2916 | 0.5768 | 0.3312 | 0.4969 | 0.5521 | 0.3257 | 0.513 | 0.7292 | 0.5629 | 0.7243 | 0.3179 | 0.5633 | 0.2498 | 0.4696 | 0.267 | 0.52 | 0.3095 | 0.4831 |
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+ | 12.4151 | 21.0 | 2247 | 11.9833 | 0.3286 | 0.6184 | 0.2991 | 0.1597 | 0.277 | 0.533 | 0.3224 | 0.4898 | 0.5452 | 0.3502 | 0.5003 | 0.7228 | 0.5478 | 0.6955 | 0.2979 | 0.5899 | 0.2414 | 0.4638 | 0.2361 | 0.4923 | 0.3197 | 0.4844 |
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+ | 12.4151 | 22.0 | 2354 | 11.9215 | 0.3408 | 0.6259 | 0.3184 | 0.142 | 0.2864 | 0.5548 | 0.3264 | 0.4893 | 0.5399 | 0.3216 | 0.4872 | 0.744 | 0.5429 | 0.6923 | 0.3578 | 0.619 | 0.2483 | 0.4585 | 0.2269 | 0.4569 | 0.3282 | 0.4729 |
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+ | 12.4151 | 23.0 | 2461 | 12.0853 | 0.3304 | 0.6162 | 0.3031 | 0.1564 | 0.2852 | 0.5542 | 0.3198 | 0.4856 | 0.5275 | 0.309 | 0.4927 | 0.7118 | 0.5404 | 0.7041 | 0.3271 | 0.5886 | 0.242 | 0.4237 | 0.2325 | 0.4492 | 0.3097 | 0.472 |
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+ | 11.6364 | 24.0 | 2568 | 11.8409 | 0.3344 | 0.622 | 0.3186 | 0.1689 | 0.2871 | 0.5485 | 0.3217 | 0.4938 | 0.5446 | 0.3457 | 0.4936 | 0.7208 | 0.5455 | 0.7126 | 0.2952 | 0.5899 | 0.2615 | 0.4638 | 0.2534 | 0.4862 | 0.3164 | 0.4707 |
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+ | 11.6364 | 25.0 | 2675 | 12.1816 | 0.3201 | 0.5981 | 0.3021 | 0.1342 | 0.2717 | 0.5455 | 0.3151 | 0.4803 | 0.5303 | 0.3205 | 0.4817 | 0.7252 | 0.5315 | 0.7023 | 0.2957 | 0.5911 | 0.2163 | 0.4415 | 0.2379 | 0.4462 | 0.3188 | 0.4707 |
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+ | 11.6364 | 26.0 | 2782 | 11.9448 | 0.3291 | 0.6113 | 0.2964 | 0.1687 | 0.2751 | 0.5635 | 0.3163 | 0.4875 | 0.5385 | 0.3434 | 0.4928 | 0.7221 | 0.5433 | 0.6919 | 0.2817 | 0.5797 | 0.2582 | 0.4746 | 0.2367 | 0.4708 | 0.3254 | 0.4756 |
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+ | 11.6364 | 27.0 | 2889 | 11.9042 | 0.322 | 0.6094 | 0.2899 | 0.1286 | 0.2739 | 0.5564 | 0.3211 | 0.4919 | 0.5404 | 0.3371 | 0.4771 | 0.7404 | 0.5306 | 0.7005 | 0.3051 | 0.5975 | 0.2411 | 0.4509 | 0.228 | 0.4769 | 0.3052 | 0.4764 |
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+ | 11.6364 | 28.0 | 2996 | 12.1391 | 0.3242 | 0.6003 | 0.3057 | 0.1342 | 0.2714 | 0.5507 | 0.3144 | 0.483 | 0.5308 | 0.3222 | 0.4825 | 0.7136 | 0.5356 | 0.6986 | 0.298 | 0.5848 | 0.2454 | 0.4487 | 0.2544 | 0.4538 | 0.2875 | 0.468 |
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+ | 11.0017 | 29.0 | 3103 | 12.0627 | 0.3371 | 0.6166 | 0.3215 | 0.1445 | 0.2846 | 0.5479 | 0.3212 | 0.4874 | 0.5441 | 0.3267 | 0.5051 | 0.7284 | 0.5411 | 0.7077 | 0.3292 | 0.6038 | 0.2528 | 0.4451 | 0.2572 | 0.4877 | 0.3052 | 0.4764 |
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+ | 11.0017 | 30.0 | 3210 | 12.3028 | 0.3353 | 0.6079 | 0.3192 | 0.158 | 0.2837 | 0.5625 | 0.315 | 0.4875 | 0.5332 | 0.2965 | 0.4917 | 0.7294 | 0.5347 | 0.6905 | 0.3534 | 0.6 | 0.246 | 0.4464 | 0.242 | 0.4662 | 0.3001 | 0.4631 |
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+ | 11.0017 | 31.0 | 3317 | 11.9750 | 0.339 | 0.6148 | 0.325 | 0.1401 | 0.2827 | 0.5603 | 0.3195 | 0.4821 | 0.5328 | 0.2975 | 0.4866 | 0.7262 | 0.5451 | 0.7063 | 0.3469 | 0.5848 | 0.2502 | 0.4522 | 0.2412 | 0.4585 | 0.3115 | 0.4622 |
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+ | 11.0017 | 32.0 | 3424 | 12.0644 | 0.3361 | 0.6158 | 0.3151 | 0.1374 | 0.2836 | 0.5539 | 0.3197 | 0.4886 | 0.5368 | 0.2821 | 0.5061 | 0.7212 | 0.5472 | 0.6982 | 0.3281 | 0.5886 | 0.2436 | 0.4612 | 0.2432 | 0.4615 | 0.3186 | 0.4747 |
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+ | 10.4746 | 33.0 | 3531 | 11.9360 | 0.3323 | 0.615 | 0.3027 | 0.1597 | 0.2821 | 0.5495 | 0.3162 | 0.4863 | 0.5366 | 0.294 | 0.4971 | 0.7228 | 0.531 | 0.7032 | 0.3396 | 0.5949 | 0.2532 | 0.4705 | 0.2255 | 0.4477 | 0.3121 | 0.4667 |
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+ | 10.4746 | 34.0 | 3638 | 11.7375 | 0.3393 | 0.6215 | 0.3145 | 0.1483 | 0.2853 | 0.5579 | 0.326 | 0.4915 | 0.5427 | 0.3199 | 0.5005 | 0.7224 | 0.5444 | 0.6968 | 0.3343 | 0.6076 | 0.2515 | 0.4638 | 0.2479 | 0.4615 | 0.3183 | 0.4836 |
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+ | 10.4746 | 35.0 | 3745 | 11.9828 | 0.3282 | 0.605 | 0.3017 | 0.1392 | 0.2717 | 0.5518 | 0.3145 | 0.4801 | 0.5305 | 0.2918 | 0.4795 | 0.7182 | 0.5313 | 0.6973 | 0.3315 | 0.5835 | 0.2456 | 0.4616 | 0.2217 | 0.4446 | 0.3108 | 0.4653 |
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+ | 10.4746 | 36.0 | 3852 | 11.8752 | 0.3302 | 0.6169 | 0.31 | 0.1597 | 0.2683 | 0.5583 | 0.3127 | 0.4814 | 0.5278 | 0.297 | 0.4793 | 0.709 | 0.5367 | 0.6968 | 0.3315 | 0.5848 | 0.2429 | 0.4402 | 0.2198 | 0.4477 | 0.32 | 0.4693 |
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+ | 10.4746 | 37.0 | 3959 | 11.9312 | 0.3304 | 0.6097 | 0.3073 | 0.1444 | 0.2765 | 0.5464 | 0.3185 | 0.4809 | 0.536 | 0.3159 | 0.4909 | 0.7086 | 0.5382 | 0.6923 | 0.3265 | 0.6013 | 0.2545 | 0.454 | 0.213 | 0.4538 | 0.3198 | 0.4787 |
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+ | 9.9527 | 38.0 | 4066 | 11.9053 | 0.3355 | 0.6135 | 0.3116 | 0.1443 | 0.283 | 0.5541 | 0.3188 | 0.4856 | 0.5333 | 0.3009 | 0.4804 | 0.7224 | 0.5382 | 0.6919 | 0.3493 | 0.5962 | 0.2481 | 0.4527 | 0.2271 | 0.4523 | 0.3151 | 0.4733 |
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+ | 9.9527 | 39.0 | 4173 | 11.9321 | 0.331 | 0.6118 | 0.3094 | 0.1417 | 0.2754 | 0.5537 | 0.313 | 0.4817 | 0.5325 | 0.3038 | 0.4847 | 0.7139 | 0.538 | 0.6995 | 0.3312 | 0.5949 | 0.2491 | 0.4549 | 0.2289 | 0.4415 | 0.3079 | 0.4716 |
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+ | 9.9527 | 40.0 | 4280 | 11.8940 | 0.3317 | 0.6135 | 0.3061 | 0.1432 | 0.276 | 0.5536 | 0.3136 | 0.4796 | 0.5283 | 0.2983 | 0.477 | 0.715 | 0.5378 | 0.7009 | 0.3298 | 0.5823 | 0.2506 | 0.4496 | 0.2308 | 0.4446 | 0.3095 | 0.464 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.52.3
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+ - Pytorch 2.7.0+cu126
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+ - Datasets 3.6.0
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+ - Tokenizers 0.21.1
config.json ADDED
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+ {
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+ "activation_dropout": 0.0,
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+ "activation_function": "silu",
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+ "anchor_image_size": null,
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+ "architectures": [
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+ "RTDetrV2ForObjectDetection"
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+ ],
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+ "attention_dropout": 0.0,
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+ "auxiliary_loss": true,
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+ "backbone": null,
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+ "backbone_config": {
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+ "depths": [
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+ 3,
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+ 4,
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+ 6,
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+ 3
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+ ],
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+ "downsample_in_bottleneck": false,
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+ "downsample_in_first_stage": false,
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+ "embedding_size": 64,
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+ "hidden_act": "relu",
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+ "hidden_sizes": [
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+ 256,
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+ 512,
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+ 1024,
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+ 2048
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+ ],
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+ "layer_type": "bottleneck",
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+ "model_type": "rt_detr_resnet",
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+ "num_channels": 3,
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+ "out_features": [
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+ "stage2",
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+ "stage3",
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+ "stage4"
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+ ],
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+ "out_indices": [
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+ 2,
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+ 3,
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+ 4
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+ ],
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+ "stage_names": [
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+ "stem",
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+ "stage1",
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+ "stage2",
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+ "stage3",
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+ "stage4"
47
+ ]
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+ },
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+ "backbone_kwargs": null,
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+ "batch_norm_eps": 1e-05,
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+ "box_noise_scale": 1.0,
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+ "d_model": 256,
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+ "decoder_activation_function": "relu",
54
+ "decoder_attention_heads": 8,
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+ "decoder_ffn_dim": 1024,
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+ "decoder_in_channels": [
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+ 256,
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+ 256,
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+ 256
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+ ],
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+ "decoder_layers": 6,
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+ "decoder_method": "default",
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+ "decoder_n_levels": 3,
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+ "decoder_n_points": 4,
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+ "decoder_offset_scale": 0.5,
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+ "disable_custom_kernels": true,
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+ "dropout": 0.0,
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+ "encode_proj_layers": [
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+ 2
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+ ],
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+ "encoder_activation_function": "gelu",
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+ "encoder_attention_heads": 8,
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+ "encoder_ffn_dim": 1024,
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+ "encoder_hidden_dim": 256,
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+ "encoder_in_channels": [
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+ 512,
77
+ 1024,
78
+ 2048
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+ ],
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+ "encoder_layers": 1,
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+ "eos_coefficient": 0.0001,
82
+ "eval_size": null,
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+ "feat_strides": [
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+ 8,
85
+ 16,
86
+ 32
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+ ],
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+ "focal_loss_alpha": 0.75,
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+ "focal_loss_gamma": 2.0,
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