--- library_name: transformers license: apache-2.0 base_model: b09501048/rtdetr2 tags: - generated_from_trainer model-index: - name: rtdetr3 results: [] --- [Visualize in Weights & Biases](https://wandb.ai/djengo890-national-taiwan-university/CVDPL_HW1_RT_DETR/runs/krauv7q7) # rtdetr3 This model is a fine-tuned version of [b09501048/rtdetr2](https://huggingface.co/b09501048/rtdetr2) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 12.0504 - Map: 0.2831 - Map 50: 0.4512 - Map 75: 0.2953 - Map Small: 0.1426 - Map Medium: 0.3859 - Map Large: 0.469 - Mar 1: 0.2299 - Mar 10: 0.441 - Mar 100: 0.4546 - Mar Small: 0.2539 - Mar Medium: 0.5608 - Mar Large: 0.6712 - Map Person: 0.716 - Mar 100 Person: 0.8309 - Map Ear: 0.357 - Mar 100 Ear: 0.459 - Map Earmuffs: 0.2616 - Mar 100 Earmuffs: 0.4676 - Map Face: 0.4488 - Mar 100 Face: 0.6417 - Map Face-guard: 0.2019 - Mar 100 Face-guard: 0.5125 - Map Face-mask-medical: 0.1874 - Mar 100 Face-mask-medical: 0.2842 - Map Foot: 0.0467 - Mar 100 Foot: 0.2941 - Map Tools: 0.0755 - Mar 100 Tools: 0.2582 - Map Glasses: 0.2358 - Mar 100 Glasses: 0.3972 - Map Gloves: 0.2782 - Mar 100 Gloves: 0.4345 - Map Helmet: 0.2651 - Mar 100 Helmet: 0.3929 - Map Hands: 0.5228 - Mar 100 Hands: 0.6237 - Map Head: 0.571 - Mar 100 Head: 0.6738 - Map Medical-suit: 0.1583 - Mar 100 Medical-suit: 0.45 - Map Shoes: 0.3526 - Mar 100 Shoes: 0.4729 - Map Safety-suit: 0.0216 - Mar 100 Safety-suit: 0.35 - Map Safety-vest: 0.1126 - Mar 100 Safety-vest: 0.1855 ## 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 adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: linear - lr_scheduler_warmup_steps: 300 - num_epochs: 5 - 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 Person | Mar 100 Person | Map Ear | Mar 100 Ear | Map Earmuffs | Mar 100 Earmuffs | Map Face | Mar 100 Face | Map Face-guard | Mar 100 Face-guard | Map Face-mask-medical | Mar 100 Face-mask-medical | Map Foot | Mar 100 Foot | Map Tools | Mar 100 Tools | Map Glasses | Mar 100 Glasses | Map Gloves | Mar 100 Gloves | Map Helmet | Mar 100 Helmet | Map Hands | Mar 100 Hands | Map Head | Mar 100 Head | Map Medical-suit | Mar 100 Medical-suit | Map Shoes | Mar 100 Shoes | Map Safety-suit | Mar 100 Safety-suit | Map Safety-vest | Mar 100 Safety-vest | |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:----------:|:---------:|:------:|:------:|:-------:|:---------:|:----------:|:---------:|:----------:|:--------------:|:-------:|:-----------:|:------------:|:----------------:|:--------:|:------------:|:--------------:|:------------------:|:---------------------:|:-------------------------:|:--------:|:------------:|:---------:|:-------------:|:-----------:|:---------------:|:----------:|:--------------:|:----------:|:--------------:|:---------:|:-------------:|:--------:|:------------:|:----------------:|:--------------------:|:---------:|:-------------:|:---------------:|:-------------------:|:---------------:|:-------------------:| | No log | 1.0 | 459 | 12.7473 | 0.2463 | 0.3958 | 0.2544 | 0.1222 | 0.3462 | 0.3923 | 0.2108 | 0.3909 | 0.404 | 0.2092 | 0.4925 | 0.6225 | 0.6449 | 0.827 | 0.3065 | 0.4 | 0.1965 | 0.4378 | 0.4368 | 0.603 | 0.1483 | 0.45 | 0.1711 | 0.2474 | 0.0568 | 0.2373 | 0.0683 | 0.2296 | 0.2028 | 0.3113 | 0.2313 | 0.3721 | 0.2246 | 0.35 | 0.5063 | 0.6106 | 0.5744 | 0.672 | 0.0043 | 0.2778 | 0.3112 | 0.4452 | 0.0066 | 0.235 | 0.0971 | 0.1613 | | 14.0301 | 2.0 | 918 | 11.8304 | 0.2764 | 0.4391 | 0.283 | 0.141 | 0.3804 | 0.4657 | 0.2313 | 0.4441 | 0.4637 | 0.244 | 0.5718 | 0.7022 | 0.6841 | 0.8373 | 0.3857 | 0.4744 | 0.2263 | 0.4865 | 0.4943 | 0.6643 | 0.2173 | 0.575 | 0.1887 | 0.3298 | 0.0288 | 0.2686 | 0.0586 | 0.2647 | 0.2346 | 0.4232 | 0.3175 | 0.4628 | 0.2462 | 0.4098 | 0.5093 | 0.6097 | 0.6284 | 0.7096 | 0.0157 | 0.3778 | 0.3542 | 0.4786 | 0.0162 | 0.34 | 0.0935 | 0.171 | | 13.9816 | 3.0 | 1377 | 12.0861 | 0.2814 | 0.4484 | 0.2909 | 0.141 | 0.3911 | 0.4422 | 0.2314 | 0.4479 | 0.4649 | 0.2391 | 0.5663 | 0.6917 | 0.7053 | 0.8295 | 0.3844 | 0.4867 | 0.2688 | 0.4703 | 0.426 | 0.6411 | 0.1494 | 0.475 | 0.1747 | 0.3035 | 0.0632 | 0.3275 | 0.0788 | 0.2598 | 0.2417 | 0.409 | 0.2273 | 0.3774 | 0.296 | 0.417 | 0.5231 | 0.6358 | 0.6 | 0.6995 | 0.1266 | 0.5167 | 0.3678 | 0.4991 | 0.0182 | 0.31 | 0.1321 | 0.2452 | | 13.4376 | 4.0 | 1836 | 12.0504 | 0.2831 | 0.4512 | 0.2953 | 0.1426 | 0.3859 | 0.469 | 0.2299 | 0.441 | 0.4546 | 0.2539 | 0.5608 | 0.6712 | 0.716 | 0.8309 | 0.357 | 0.459 | 0.2616 | 0.4676 | 0.4488 | 0.6417 | 0.2019 | 0.5125 | 0.1874 | 0.2842 | 0.0467 | 0.2941 | 0.0755 | 0.2582 | 0.2358 | 0.3972 | 0.2782 | 0.4345 | 0.2651 | 0.3929 | 0.5228 | 0.6237 | 0.571 | 0.6738 | 0.1583 | 0.45 | 0.3526 | 0.4729 | 0.0216 | 0.35 | 0.1126 | 0.1855 | | 13.0503 | 5.0 | 2295 | 12.2470 | 0.2781 | 0.4505 | 0.2859 | 0.1352 | 0.3917 | 0.4434 | 0.2417 | 0.4386 | 0.4518 | 0.2304 | 0.5572 | 0.6509 | 0.7016 | 0.8247 | 0.3341 | 0.4344 | 0.2608 | 0.4919 | 0.4105 | 0.6234 | 0.1222 | 0.4375 | 0.1875 | 0.2825 | 0.0837 | 0.302 | 0.0757 | 0.2683 | 0.2379 | 0.3938 | 0.2675 | 0.4119 | 0.295 | 0.4045 | 0.5211 | 0.6243 | 0.5795 | 0.6805 | 0.131 | 0.4833 | 0.3578 | 0.4833 | 0.0333 | 0.345 | 0.1284 | 0.1887 | ### Framework versions - Transformers 4.46.0.dev0 - Pytorch 2.4.1+cu121 - Datasets 3.0.1 - Tokenizers 0.20.1