Rtdetr v2 R50 Finetune 18

--- library_name: transformers license: apache-2.0 base_model: PekingU/rtdetr_v2_r50vd tags: - generated_from_trainer model-index: - name: rtdetr-v2-r50-finetune-18 results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> # rtdetr-v2-r50-finetune-18 This model is a fine-tuned version of [PekingU/rtdetr_v2_r50vd](https://huggingface.co/PekingU/rtdetr_v2_r50vd) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 6.2140 - Map: 0.5792 - Map 50: 0.9062 - Map 75: 0.6927 - Map Small: 0.5499 - Map Medium: 0.6586 - Map Large: -1.0 - Mar 1: 0.3485 - Mar 10: 0.665 - Mar 100: 0.7061 - Mar Small: 0.6766 - Mar Medium: 0.7816 - Mar Large: -1.0 - Map Artemia: 0.5792 - Mar 100 Artemia: 0.7061 ## 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: linear - lr_scheduler_warmup_steps: 300 - num_epochs: 70 ### 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 Artemia | Mar 100 Artemia | |:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:---------:|:----------:|:---------:|:------:|:------:|:-------:|:---------:|:----------:|:---------:|:-----------:|:---------------:| | No log | 1.0 | 250 | 14.9156 | 0.2677 | 0.5009 | 0.2541 | 0.1906 | 0.4855 | -1.0 | 0.3037 | 0.605 | 0.6642 | 0.5866 | 0.7708 | -1.0 | 0.2677 | 0.6642 | | 177.9373 | 2.0 | 500 | 8.5364 | 0.4833 | 0.8728 | 0.4873 | 0.4202 | 0.5904 | -1.0 | 0.3688 | 0.59 | 0.6455 | 0.5876 | 0.7255 | -1.0 | 0.4833 | 0.6455 | | 177.9373 | 3.0 | 750 | 7.9292 | 0.508 | 0.8772 | 0.5383 | 0.4318 | 0.6172 | -1.0 | 0.3879 | 0.5947 | 0.6498 | 0.5925 | 0.7285 | -1.0 | 0.508 | 0.6498 | | 13.8839 | 4.0 | 1000 | 8.0375 | 0.4786 | 0.856...