Rtdetr v2 R18 Final

--- library_name: transformers license: apache-2.0 base_model: PekingU/rtdetr_v2_r18vd tags: - generated_from_trainer model-index: - name: rtdetr-v2-r18-final 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-r18-final This model is a fine-tuned version of [PekingU/rtdetr_v2_r18vd](https://huggingface.co/PekingU/rtdetr_v2_r18vd) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 5.1520 - Map: 0.3649 - Map 50: 0.6288 - Map 75: 0.4056 - Map Small: 0.3424 - Map Medium: 0.4806 - Map Large: -1.0 - Mar 1: 0.2595 - Mar 10: 0.6168 - Mar 100: 0.6197 - Mar Small: 0.5986 - Mar Medium: 0.6736 - Mar Large: -1.0 - Map Artemia: 0.3649 - Mar 100 Artemia: 0.6197 ## 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: 80 ### 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 | 8.9989 | 0.228 | 0.4228 | 0.2165 | 0.1636 | 0.3911 | -1.0 | 0.2614 | 0.5234 | 0.6016 | 0.5059 | 0.7336 | -1.0 | 0.228 | 0.6016 | | 72.6973 | 2.0 | 500 | 5.6413 | 0.4119 | 0.743 | 0.4161 | 0.3218 | 0.5456 | -1.0 | 0.3555 | 0.5785 | 0.638 | 0.5892 | 0.7058 | -1.0 | 0.4119 | 0.638 | | 72.6973 | 3.0 | 750 | 5.3121 | 0.4655 | 0.8136 | 0.4693 | 0.3578 | 0.5948 | -1.0 | 0.3682 | 0.5944 | 0.6567 | 0.5952 | 0.7409 | -1.0 | 0.4655 | 0.6567 | | 9.0229 | 4.0 | 1000 | 5.3701 | 0.4621 | 0.8186 | 0.4747 | 0....