--- license: apache-2.0 base_model: PekingU/rtdetr_r50vd_coco_o365 tags: - generated_from_trainer model-index: - name: law-game-evidence-replacement-finetune results: [] --- # law-game-evidence-replacement-finetune This model is a fine-tuned version of [PekingU/rtdetr_r50vd_coco_o365](https://huggingface.co/PekingU/rtdetr_r50vd_coco_o365) on an unknown dataset. It achieves the following results on the evaluation set: - eval_loss: 3.4253 - eval_map: 0.8264 - eval_map_50: 0.8488 - eval_map_75: 0.8441 - eval_map_small: 0.5688 - eval_map_medium: 0.9527 - eval_map_large: 0.8547 - eval_mar_1: 0.7043 - eval_mar_10: 0.9575 - eval_mar_100: 0.9727 - eval_mar_small: 0.5949 - eval_mar_medium: 0.9738 - eval_mar_large: 0.9894 - eval_map_evidence: -1.0 - eval_mar_100_evidence: -1.0 - eval_map_ambulance: 0.9802 - eval_mar_100_ambulance: 0.9899 - eval_map_artificial_target: 0.9267 - eval_mar_100_artificial_target: 0.9572 - eval_map_cartridge: 0.9742 - eval_mar_100_cartridge: 0.9949 - eval_map_gun: 0.9165 - eval_mar_100_gun: 0.9403 - eval_map_knife: 0.8599 - eval_mar_100_knife: 0.931 - eval_map_police: 0.9935 - eval_mar_100_police: 0.9959 - eval_map_traffic: 0.9586 - eval_mar_100_traffic: 0.9726 - eval_map_traffic_cone: 0.0013 - eval_mar_100_traffic_cone: 1.0 - eval_runtime: 50.5267 - eval_samples_per_second: 16.467 - eval_steps_per_second: 2.058 - epoch: 28.0 - step: 5152 ## 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: 16 - eval_batch_size: 8 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_steps: 300 - num_epochs: 50 ### Framework versions - Transformers 4.44.0.dev0 - Pytorch 2.3.1+cu121 - Tokenizers 0.19.1