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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_v2_r18vd
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+ tags:
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+ - generated_from_trainer
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+ model-index:
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+ - name: kvasir_seg_rtdetrv2_r18_test_fps
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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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+ # kvasir_seg_rtdetrv2_r18_test_fps
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+
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+ This model is a fine-tuned version of [PekingU/rtdetr_v2_r18vd](https://huggingface.co/PekingU/rtdetr_v2_r18vd) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 5.7736
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+ - Map: 0.6786
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+ - Map 50: 0.865
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+ - Map 75: 0.7285
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+ - Map Small: 0.0
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+ - Map Medium: 0.5729
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+ - Map Large: 0.6933
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+ - Mar 1: 0.6607
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+ - Mar 10: 0.8706
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+ - Mar 100: 0.9114
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+ - Mar Small: 0.0
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+ - Mar Medium: 0.79
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+ - Mar Large: 0.922
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+ - Map Polyp: 0.6786
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+ - Mar 100 Polyp: 0.9114
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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: 0.0001
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+ - train_batch_size: 8
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+ - eval_batch_size: 1
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+ - seed: 42
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+ - optimizer: Use 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: cosine
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+ - lr_scheduler_warmup_steps: 300
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+ - num_epochs: 10
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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 Polyp | Mar 100 Polyp |
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+ |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:----------:|:---------:|:------:|:------:|:-------:|:---------:|:----------:|:---------:|:---------:|:-------------:|
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+ | 222.0855 | 1.0 | 100 | 27.8979 | 0.2324 | 0.3276 | 0.2381 | 0.0 | 0.0033 | 0.2491 | 0.4327 | 0.6583 | 0.7569 | 0.0 | 0.47 | 0.775 | 0.2324 | 0.7569 |
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+ | 21.4558 | 2.0 | 200 | 8.5908 | 0.4453 | 0.6029 | 0.4705 | 0.0 | 0.2753 | 0.4596 | 0.6161 | 0.7815 | 0.872 | 0.0 | 0.71 | 0.8845 | 0.4453 | 0.872 |
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+ | 11.9198 | 3.0 | 300 | 7.3897 | 0.559 | 0.7445 | 0.5928 | 0.0 | 0.3981 | 0.5748 | 0.6156 | 0.8218 | 0.8806 | 0.0 | 0.74 | 0.892 | 0.559 | 0.8806 |
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+ | 10.1107 | 4.0 | 400 | 6.7691 | 0.5087 | 0.691 | 0.5261 | 0.0 | 0.258 | 0.53 | 0.6185 | 0.8047 | 0.8744 | 0.0 | 0.61 | 0.892 | 0.5087 | 0.8744 |
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+ | 8.9974 | 5.0 | 500 | 6.1887 | 0.6247 | 0.7927 | 0.6818 | 0.0 | 0.51 | 0.6464 | 0.6682 | 0.8346 | 0.8872 | 0.0 | 0.69 | 0.9015 | 0.6247 | 0.8872 |
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+ | 8.4837 | 6.0 | 600 | 6.0117 | 0.6313 | 0.82 | 0.6738 | 0.0 | 0.4952 | 0.6465 | 0.627 | 0.8502 | 0.9028 | 0.0 | 0.74 | 0.9155 | 0.6313 | 0.9028 |
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+ | 7.9083 | 7.0 | 700 | 6.0504 | 0.6328 | 0.8234 | 0.6877 | 0.0 | 0.5697 | 0.6459 | 0.6412 | 0.8545 | 0.891 | 0.0 | 0.77 | 0.9015 | 0.6328 | 0.891 |
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+ | 7.4364 | 8.0 | 800 | 5.9616 | 0.6493 | 0.8454 | 0.6945 | 0.0 | 0.6155 | 0.6611 | 0.6445 | 0.8635 | 0.9033 | 0.0 | 0.78 | 0.914 | 0.6493 | 0.9033 |
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+ | 7.2255 | 9.0 | 900 | 5.7790 | 0.6767 | 0.8628 | 0.7297 | 0.0 | 0.5687 | 0.6914 | 0.663 | 0.8739 | 0.9047 | 0.0 | 0.79 | 0.915 | 0.6767 | 0.9047 |
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+ | 6.9854 | 10.0 | 1000 | 5.7736 | 0.6786 | 0.865 | 0.7285 | 0.0 | 0.5729 | 0.6933 | 0.6607 | 0.8706 | 0.9114 | 0.0 | 0.79 | 0.922 | 0.6786 | 0.9114 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.53.0.dev0
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+ - Pytorch 2.7.1+cu126
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+ - Datasets 3.6.0
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+ - Tokenizers 0.21.1
runs/Jun22_11-08-58_itri-kiosk-pt/events.out.tfevents.1750561980.itri-kiosk-pt.1129722.1 ADDED
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+ size 1086