--- library_name: transformers license: apache-2.0 base_model: PekingU/rtdetr_r50vd tags: - object-detection - vision - generated_from_trainer model-index: - name: suas-2025-rtdetr-finetuned results: [] --- # suas-2025-rtdetr-finetuned This model is a fine-tuned version of [PekingU/rtdetr_r50vd](https://huggingface.co/PekingU/rtdetr_r50vd) on the mfly-auton/suas-2025-synthetic-data dataset. It achieves the following results on the evaluation set: - Loss: 3.8868 - Map: 0.8924 - Map 50: 0.9568 - Map 75: 0.9554 - Map Small: 0.8115 - Map Medium: 0.9048 - Map Large: 0.9511 - Mar 1: 0.8296 - Mar 10: 0.938 - Mar 100: 0.9407 - Mar Small: 0.8752 - Mar Medium: 0.9535 - Mar Large: 0.9911 - Map Baseball-bat: 0.8962 - Mar 100 Baseball-bat: 0.9382 - Map Basketball: 0.8344 - Mar 100 Basketball: 0.9077 - Map Car: -1.0 - Mar 100 Car: -1.0 - Map Football: 0.814 - Mar 100 Football: 0.8709 - Map Human: 0.9172 - Mar 100 Human: 0.9686 - Map Luggage: 0.8623 - Mar 100 Luggage: 0.9241 - Map Mattress: 0.9809 - Mar 100 Mattress: 0.9971 - Map Motorcycle: 0.9393 - Mar 100 Motorcycle: 0.9751 - Map Skis: 0.8496 - Mar 100 Skis: 0.9692 - Map Snowboard: 0.9857 - Mar 100 Snowboard: 0.9947 - Map Soccer-ball: 0.8382 - Mar 100 Soccer-ball: 0.8755 - Map Stop-sign: 0.9735 - Mar 100 Stop-sign: 0.9957 - Map Tennis-racket: 0.9007 - Mar 100 Tennis-racket: 0.9245 - Map Umbrella: 0.8994 - Mar 100 Umbrella: 0.9775 - Map Volleyball: 0.8024 - Mar 100 Volleyball: 0.8507 ## 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: 3e-05 - train_batch_size: 8 - eval_batch_size: 8 - seed: 1337 - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: linear - num_epochs: 5.0 - mixed_precision_training: Native AMP ### 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 Baseball-bat | Mar 100 Baseball-bat | Map Basketball | Mar 100 Basketball | Map Car | Mar 100 Car | Map Football | Mar 100 Football | Map Human | Mar 100 Human | Map Luggage | Mar 100 Luggage | Map Mattress | Mar 100 Mattress | Map Motorcycle | Mar 100 Motorcycle | Map Skis | Mar 100 Skis | Map Snowboard | Mar 100 Snowboard | Map Soccer-ball | Mar 100 Soccer-ball | Map Stop-sign | Mar 100 Stop-sign | Map Tennis-racket | Mar 100 Tennis-racket | Map Umbrella | Mar 100 Umbrella | Map Volleyball | Mar 100 Volleyball | |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:----------:|:---------:|:------:|:------:|:-------:|:---------:|:----------:|:---------:|:----------------:|:--------------------:|:--------------:|:------------------:|:-------:|:-----------:|:------------:|:----------------:|:---------:|:-------------:|:-----------:|:---------------:|:------------:|:----------------:|:--------------:|:------------------:|:--------:|:------------:|:-------------:|:-----------------:|:---------------:|:-------------------:|:-------------:|:-----------------:|:-----------------:|:---------------------:|:------------:|:----------------:|:--------------:|:------------------:| | 12.0474 | 1.0 | 438 | 5.5119 | 0.8067 | 0.8868 | 0.8817 | 0.7597 | 0.7886 | 0.8834 | 0.7817 | 0.9168 | 0.924 | 0.8348 | 0.9511 | 0.9848 | 0.7992 | 0.9114 | 0.819 | 0.901 | -1.0 | -1.0 | 0.7627 | 0.8381 | 0.6589 | 0.9657 | 0.8118 | 0.9173 | 0.9643 | 0.9961 | 0.8513 | 0.9658 | 0.5388 | 0.9767 | 0.9801 | 0.9925 | 0.7934 | 0.85 | 0.9652 | 0.988 | 0.8307 | 0.9057 | 0.8198 | 0.9603 | 0.6983 | 0.7671 | | 6.1205 | 2.0 | 876 | 5.0519 | 0.8186 | 0.8885 | 0.8836 | 0.746 | 0.7754 | 0.902 | 0.7791 | 0.9033 | 0.9094 | 0.8072 | 0.9373 | 0.9872 | 0.8735 | 0.9189 | 0.8175 | 0.9172 | -1.0 | -1.0 | 0.7607 | 0.8174 | 0.798 | 0.9653 | 0.8087 | 0.8941 | 0.9531 | 0.9942 | 0.7115 | 0.9665 | 0.7689 | 0.9508 | 0.9767 | 0.9957 | 0.7882 | 0.846 | 0.92 | 0.9799 | 0.8979 | 0.9208 | 0.7901 | 0.9309 | 0.5955 | 0.6338 | | 5.3217 | 3.0 | 1314 | 4.0739 | 0.8811 | 0.9513 | 0.9499 | 0.7797 | 0.8841 | 0.9549 | 0.8259 | 0.9337 | 0.9374 | 0.8626 | 0.9518 | 0.9937 | 0.8664 | 0.9269 | 0.8426 | 0.9086 | -1.0 | -1.0 | 0.7995 | 0.8595 | 0.891 | 0.9688 | 0.8574 | 0.9292 | 0.9881 | 0.9998 | 0.9232 | 0.9719 | 0.8199 | 0.9958 | 0.9816 | 0.9932 | 0.82 | 0.862 | 0.979 | 0.994 | 0.8971 | 0.9198 | 0.8925 | 0.9689 | 0.777 | 0.8258 | | 4.7931 | 4.0 | 1752 | 3.8984 | 0.8943 | 0.9605 | 0.9589 | 0.8046 | 0.9139 | 0.9535 | 0.8289 | 0.9363 | 0.9404 | 0.8726 | 0.9571 | 0.9849 | 0.8889 | 0.9341 | 0.8321 | 0.9053 | -1.0 | -1.0 | 0.809 | 0.8622 | 0.9072 | 0.9685 | 0.8876 | 0.9389 | 0.9796 | 0.9993 | 0.9379 | 0.9757 | 0.8801 | 0.96 | 0.9855 | 0.9972 | 0.8379 | 0.8745 | 0.9811 | 0.994 | 0.9046 | 0.9302 | 0.8907 | 0.9722 | 0.7979 | 0.8531 | | 4.634 | 5.0 | 2190 | 3.8868 | 0.8924 | 0.9568 | 0.9554 | 0.8115 | 0.9048 | 0.9511 | 0.8296 | 0.938 | 0.9407 | 0.8752 | 0.9535 | 0.9911 | 0.8962 | 0.9382 | 0.8344 | 0.9077 | -1.0 | -1.0 | 0.814 | 0.8709 | 0.9172 | 0.9686 | 0.8623 | 0.9241 | 0.9809 | 0.9971 | 0.9393 | 0.9751 | 0.8496 | 0.9692 | 0.9857 | 0.9947 | 0.8382 | 0.8755 | 0.9735 | 0.9957 | 0.9007 | 0.9245 | 0.8994 | 0.9775 | 0.8024 | 0.8507 | ### Framework versions - Transformers 4.47.0 - Pytorch 2.5.1+cu124 - Datasets 3.1.0 - Tokenizers 0.21.0