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apple-detection-with-rtdetr-rd50vd-coco-o365

Object Detection
Transformers
Safetensors
rt_detr
Generated from Trainer
Inference Endpoints
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  2. model.safetensors +1 -1
README.md ADDED
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+ ---
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+ library_name: transformers
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+ license: apache-2.0
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+ base_model: PekingU/rtdetr_r50vd_coco_o365
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+ tags:
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+ - generated_from_trainer
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+ model-index:
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+ - name: apple-detection-with-rtdetr-rd50vd-coco-o365
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+ results: []
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+ ---
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+
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+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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+ should probably proofread and complete it, then remove this comment. -->
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+
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+ # apple-detection-with-rtdetr-rd50vd-coco-o365
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+
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+ 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.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 5.7891
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+ - Map: 0.8588
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+ - Map 50: 0.9441
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+ - Map 75: 0.9232
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+ - Map Small: -1.0
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+ - Map Medium: -1.0
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+ - Map Large: 0.8593
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+ - Mar 1: 0.2596
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+ - Mar 10: 0.7771
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+ - Mar 100: 0.94
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+ - Mar Small: -1.0
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+ - Mar Medium: -1.0
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+ - Mar Large: 0.94
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+ - Map Apple: 0.8588
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+ - Mar 100 Apple: 0.94
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 5e-05
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+ - train_batch_size: 8
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+ - eval_batch_size: 8
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+ - seed: 42
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+ - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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+ - lr_scheduler_type: linear
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+ - lr_scheduler_warmup_steps: 300
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+ - num_epochs: 100
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+ - mixed_precision_training: Native AMP
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+
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+ ### Training results
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+
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+ | 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 Apple | Mar 100 Apple |
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+ |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:----------:|:---------:|:------:|:------:|:-------:|:---------:|:----------:|:---------:|:---------:|:-------------:|
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+ | No log | 1.0 | 169 | 14.5718 | 0.1228 | 0.2421 | 0.1084 | -1.0 | 0.0157 | 0.1399 | 0.1375 | 0.3146 | 0.6275 | -1.0 | 0.5333 | 0.6277 | 0.1228 | 0.6275 |
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+ | No log | 2.0 | 338 | 9.2170 | 0.5022 | 0.692 | 0.5452 | -1.0 | 0.3272 | 0.5035 | 0.225 | 0.5618 | 0.8138 | -1.0 | 0.9333 | 0.8136 | 0.5022 | 0.8138 |
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+ | 30.1672 | 3.0 | 507 | 8.8104 | 0.5503 | 0.6829 | 0.6163 | -1.0 | 0.4455 | 0.5516 | 0.2309 | 0.6075 | 0.8643 | -1.0 | 0.9 | 0.8642 | 0.5503 | 0.8643 |
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+ | 30.1672 | 4.0 | 676 | 8.0371 | 0.6275 | 0.7697 | 0.7078 | -1.0 | 0.4374 | 0.6279 | 0.2427 | 0.6525 | 0.8602 | -1.0 | 0.9333 | 0.86 | 0.6275 | 0.8602 |
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+ | 30.1672 | 5.0 | 845 | 7.0432 | 0.6851 | 0.807 | 0.778 | -1.0 | 0.521 | 0.6858 | 0.2448 | 0.6939 | 0.8754 | -1.0 | 0.7667 | 0.8757 | 0.6851 | 0.8754 |
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+ | 12.3777 | 6.0 | 1014 | 7.4024 | 0.7262 | 0.8607 | 0.8231 | -1.0 | 0.4729 | 0.729 | 0.2437 | 0.6998 | 0.8842 | -1.0 | 0.9 | 0.8842 | 0.7262 | 0.8842 |
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+ | 12.3777 | 7.0 | 1183 | 7.6969 | 0.7006 | 0.8097 | 0.7746 | -1.0 | 0.417 | 0.7031 | 0.2443 | 0.7104 | 0.8897 | -1.0 | 0.7667 | 0.89 | 0.7006 | 0.8897 |
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+ | 12.3777 | 8.0 | 1352 | 7.0771 | 0.7536 | 0.8664 | 0.8397 | -1.0 | 0.7023 | 0.7541 | 0.249 | 0.7151 | 0.891 | -1.0 | 0.9333 | 0.8909 | 0.7536 | 0.891 |
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+ | 11.4378 | 9.0 | 1521 | 7.6821 | 0.7493 | 0.8728 | 0.8397 | -1.0 | 0.5096 | 0.7509 | 0.2484 | 0.7257 | 0.9009 | -1.0 | 0.9 | 0.9009 | 0.7493 | 0.9009 |
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+ | 11.4378 | 10.0 | 1690 | 7.0789 | 0.7901 | 0.9168 | 0.8872 | -1.0 | 0.5995 | 0.7907 | 0.2459 | 0.7272 | 0.8985 | -1.0 | 0.8667 | 0.8985 | 0.7901 | 0.8985 |
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+ | 11.4378 | 11.0 | 1859 | 7.1990 | 0.7908 | 0.894 | 0.8677 | -1.0 | 0.6183 | 0.7918 | 0.2503 | 0.7353 | 0.9113 | -1.0 | 0.9 | 0.9114 | 0.7908 | 0.9113 |
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+ | 10.5157 | 12.0 | 2028 | 6.6454 | 0.7664 | 0.8872 | 0.8547 | -1.0 | 0.5614 | 0.7677 | 0.248 | 0.7315 | 0.8994 | -1.0 | 0.8667 | 0.8995 | 0.7664 | 0.8994 |
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+ | 10.5157 | 13.0 | 2197 | 7.4329 | 0.7401 | 0.8425 | 0.812 | -1.0 | 0.7072 | 0.7409 | 0.2485 | 0.7313 | 0.902 | -1.0 | 0.9 | 0.902 | 0.7401 | 0.902 |
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+ | 10.5157 | 14.0 | 2366 | 6.7330 | 0.8094 | 0.9061 | 0.8781 | -1.0 | 0.7158 | 0.8098 | 0.2523 | 0.7525 | 0.9168 | -1.0 | 0.9 | 0.9169 | 0.8094 | 0.9168 |
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+ | 9.8125 | 15.0 | 2535 | 6.5761 | 0.8023 | 0.9071 | 0.8815 | -1.0 | 0.7502 | 0.8029 | 0.2528 | 0.7456 | 0.9108 | -1.0 | 0.8667 | 0.9109 | 0.8023 | 0.9108 |
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+ | 9.8125 | 16.0 | 2704 | 6.5281 | 0.818 | 0.919 | 0.8961 | -1.0 | 0.6455 | 0.8185 | 0.252 | 0.7501 | 0.9141 | -1.0 | 0.9 | 0.9141 | 0.818 | 0.9141 |
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+ | 9.8125 | 17.0 | 2873 | 6.6390 | 0.8178 | 0.9158 | 0.8959 | -1.0 | 0.7281 | 0.8189 | 0.251 | 0.7423 | 0.9179 | -1.0 | 0.9 | 0.918 | 0.8178 | 0.9179 |
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+ | 9.4182 | 18.0 | 3042 | 6.4843 | 0.8341 | 0.9298 | 0.9035 | -1.0 | 0.6102 | 0.8347 | 0.2507 | 0.7526 | 0.9203 | -1.0 | 0.8667 | 0.9205 | 0.8341 | 0.9203 |
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+ | 9.4182 | 19.0 | 3211 | 7.2777 | 0.7999 | 0.9018 | 0.8787 | -1.0 | 0.6338 | 0.8015 | 0.249 | 0.7413 | 0.9173 | -1.0 | 0.9 | 0.9173 | 0.7999 | 0.9173 |
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+ | 9.4182 | 20.0 | 3380 | 6.6993 | 0.8291 | 0.9234 | 0.8972 | -1.0 | 0.7493 | 0.8301 | 0.2516 | 0.7537 | 0.9245 | -1.0 | 0.9333 | 0.9245 | 0.8291 | 0.9245 |
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+ | 9.0821 | 21.0 | 3549 | 6.8164 | 0.8154 | 0.9222 | 0.9018 | -1.0 | 0.7889 | 0.8158 | 0.2533 | 0.744 | 0.9167 | -1.0 | 0.9333 | 0.9166 | 0.8154 | 0.9167 |
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+ | 9.0821 | 22.0 | 3718 | 6.7705 | 0.8158 | 0.9272 | 0.9034 | -1.0 | 0.6072 | 0.8169 | 0.2473 | 0.7421 | 0.9116 | -1.0 | 0.9 | 0.9117 | 0.8158 | 0.9116 |
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+ | 9.0821 | 23.0 | 3887 | 5.8021 | 0.838 | 0.9356 | 0.9121 | -1.0 | 0.6007 | 0.8391 | 0.2505 | 0.7538 | 0.9247 | -1.0 | 0.9 | 0.9248 | 0.838 | 0.9247 |
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+ | 8.7442 | 24.0 | 4056 | 6.3070 | 0.8475 | 0.9312 | 0.9098 | -1.0 | 0.7521 | 0.8481 | 0.2531 | 0.7582 | 0.9282 | -1.0 | 0.9333 | 0.9282 | 0.8475 | 0.9282 |
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+ | 8.7442 | 25.0 | 4225 | 5.7625 | 0.8491 | 0.9336 | 0.9136 | -1.0 | 0.7109 | 0.8498 | 0.2511 | 0.7639 | 0.9285 | -1.0 | 0.9333 | 0.9285 | 0.8491 | 0.9285 |
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+ | 8.7442 | 26.0 | 4394 | 5.9863 | 0.8284 | 0.9285 | 0.9072 | -1.0 | 0.5891 | 0.8295 | 0.2525 | 0.7493 | 0.9185 | -1.0 | 0.7667 | 0.9188 | 0.8284 | 0.9185 |
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+ | 8.3969 | 27.0 | 4563 | 6.0623 | 0.8271 | 0.9343 | 0.9078 | -1.0 | 0.5669 | 0.8277 | 0.2521 | 0.7518 | 0.9097 | -1.0 | 0.8 | 0.91 | 0.8271 | 0.9097 |
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+ | 8.3969 | 28.0 | 4732 | 6.2344 | 0.8329 | 0.9302 | 0.9033 | -1.0 | 0.5902 | 0.8336 | 0.2519 | 0.7548 | 0.9247 | -1.0 | 0.9 | 0.9248 | 0.8329 | 0.9247 |
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+ | 8.3969 | 29.0 | 4901 | 6.1610 | 0.8294 | 0.9177 | 0.8965 | -1.0 | 0.6745 | 0.8304 | 0.2503 | 0.7544 | 0.9315 | -1.0 | 0.9 | 0.9315 | 0.8294 | 0.9315 |
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+ | 8.2127 | 30.0 | 5070 | 6.5000 | 0.8297 | 0.9219 | 0.9001 | -1.0 | 0.6378 | 0.8305 | 0.2508 | 0.7541 | 0.9225 | -1.0 | 0.8667 | 0.9227 | 0.8297 | 0.9225 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.49.0.dev0
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+ - Pytorch 2.5.1+cu121
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+ - Tokenizers 0.21.0
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