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rt_detrv2_finetuned_trashify_box_detector_v1

Object Detection
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rt_detr_v2
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End of training

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  1. README.md +45 -45
  2. config.json +1 -1
  3. model.safetensors +1 -1
  4. training_args.bin +2 -2
README.md CHANGED
@@ -5,44 +5,44 @@ base_model: PekingU/rtdetr_v2_r50vd
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  tags:
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  - generated_from_trainer
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  model-index:
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- - name: rt_detrv2_finetuned_trashify_box_detector_v1
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  results: []
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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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- # rt_detrv2_finetuned_trashify_box_detector_v1
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  This model is a fine-tuned version of [PekingU/rtdetr_v2_r50vd](https://huggingface.co/PekingU/rtdetr_v2_r50vd) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 10.5656
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- - Map: 0.464
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- - Map 50: 0.6416
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- - Map 75: 0.5044
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- - Map Small: 0.0536
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- - Map Medium: 0.0797
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- - Map Large: 0.4902
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- - Mar 1: 0.5143
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- - Mar 10: 0.6661
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- - Mar 100: 0.7398
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- - Mar Small: 0.35
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- - Mar Medium: 0.4801
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- - Mar Large: 0.7745
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- - Map Bin: 0.6777
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- - Mar 100 Bin: 0.8596
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- - Map Hand: 0.4888
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- - Mar 100 Hand: 0.7716
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- - Map Not Bin: 0.1536
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- - Mar 100 Not Bin: 0.6286
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- - Map Not Hand: -1.0
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- - Mar 100 Not Hand: -1.0
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- - Map Not Trash: 0.2042
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- - Mar 100 Not Trash: 0.6056
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- - Map Trash: 0.3921
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- - Mar 100 Trash: 0.7071
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- - Map Trash Arm: 0.8673
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- - Mar 100 Trash Arm: 0.8667
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  ## Model description
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@@ -73,23 +73,23 @@ The following hyperparameters were used during training:
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  ### Training results
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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 Bin | Mar 100 Bin | Map Hand | Mar 100 Hand | Map Not Bin | Mar 100 Not Bin | Map Not Hand | Mar 100 Not Hand | Map Not Trash | Mar 100 Not Trash | Map Trash | Mar 100 Trash | Map Trash Arm | Mar 100 Trash Arm |
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- |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:----------:|:---------:|:------:|:------:|:-------:|:---------:|:----------:|:---------:|:-------:|:-----------:|:--------:|:------------:|:-----------:|:---------------:|:------------:|:----------------:|:-------------:|:-----------------:|:---------:|:-------------:|:-------------:|:-----------------:|
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- | 187.7449 | 1.0 | 50 | 76.7837 | 0.0758 | 0.142 | 0.0703 | 0.0 | 0.0145 | 0.0786 | 0.1331 | 0.2875 | 0.3285 | 0.0 | 0.1858 | 0.3657 | 0.1694 | 0.644 | 0.1982 | 0.35 | 0.0103 | 0.4286 | -1.0 | -1.0 | 0.002 | 0.1708 | 0.075 | 0.3779 | 0.0 | 0.0 |
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- | 62.3477 | 2.0 | 100 | 24.7528 | 0.1999 | 0.3065 | 0.186 | 0.0 | 0.056 | 0.2109 | 0.3267 | 0.5336 | 0.5503 | 0.0 | 0.1756 | 0.5765 | 0.2835 | 0.7525 | 0.4412 | 0.6922 | 0.0064 | 0.3357 | -1.0 | -1.0 | 0.1136 | 0.3042 | 0.1756 | 0.6841 | 0.1789 | 0.5333 |
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- | 25.8089 | 3.0 | 150 | 14.7906 | 0.2551 | 0.3877 | 0.276 | 0.0 | 0.0733 | 0.2665 | 0.3814 | 0.5903 | 0.6508 | 0.0 | 0.3176 | 0.6945 | 0.2075 | 0.866 | 0.461 | 0.6892 | 0.0172 | 0.5071 | -1.0 | -1.0 | 0.0982 | 0.4111 | 0.1641 | 0.6646 | 0.5827 | 0.7667 |
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- | 18.0845 | 4.0 | 200 | 11.7929 | 0.3316 | 0.4912 | 0.3748 | 0.05 | 0.0913 | 0.3544 | 0.4116 | 0.6086 | 0.688 | 0.1 | 0.5091 | 0.7201 | 0.4974 | 0.8674 | 0.5367 | 0.7853 | 0.0997 | 0.6286 | -1.0 | -1.0 | 0.1815 | 0.4653 | 0.2816 | 0.6814 | 0.3929 | 0.7 |
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- | 15.2751 | 5.0 | 250 | 11.5743 | 0.3691 | 0.5764 | 0.3935 | 0.15 | 0.0582 | 0.3909 | 0.4324 | 0.5942 | 0.6722 | 0.15 | 0.3432 | 0.7168 | 0.5633 | 0.8518 | 0.5121 | 0.7951 | 0.0899 | 0.5857 | -1.0 | -1.0 | 0.1651 | 0.5153 | 0.3176 | 0.6522 | 0.5665 | 0.6333 |
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- | 13.6233 | 6.0 | 300 | 10.9435 | 0.424 | 0.6113 | 0.4833 | 0.0889 | 0.0624 | 0.4464 | 0.5064 | 0.6589 | 0.731 | 0.3 | 0.3568 | 0.7686 | 0.6258 | 0.8617 | 0.5329 | 0.7676 | 0.1067 | 0.6143 | -1.0 | -1.0 | 0.1775 | 0.5889 | 0.3769 | 0.6867 | 0.7243 | 0.8667 |
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- | 12.4361 | 7.0 | 350 | 10.4613 | 0.4421 | 0.6414 | 0.509 | 0.0667 | 0.0751 | 0.4698 | 0.4951 | 0.6401 | 0.7209 | 0.2 | 0.3869 | 0.7596 | 0.6413 | 0.8915 | 0.4859 | 0.7676 | 0.1556 | 0.6214 | -1.0 | -1.0 | 0.221 | 0.5819 | 0.4148 | 0.6965 | 0.7338 | 0.7667 |
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- | 11.6579 | 8.0 | 400 | 10.5329 | 0.4304 | 0.6103 | 0.4732 | 0.0354 | 0.0619 | 0.4564 | 0.4889 | 0.6422 | 0.7183 | 0.35 | 0.2438 | 0.7635 | 0.6411 | 0.8582 | 0.5113 | 0.7725 | 0.1577 | 0.4857 | -1.0 | -1.0 | 0.1848 | 0.5889 | 0.3841 | 0.7044 | 0.7031 | 0.9 |
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- | 11.0091 | 9.0 | 450 | 10.6710 | 0.4553 | 0.6325 | 0.5138 | 0.0667 | 0.0794 | 0.4824 | 0.5038 | 0.6475 | 0.7273 | 0.4 | 0.3267 | 0.7714 | 0.6649 | 0.8638 | 0.48 | 0.7618 | 0.1481 | 0.5571 | -1.0 | -1.0 | 0.2132 | 0.5986 | 0.4013 | 0.7159 | 0.8243 | 0.8667 |
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- | 10.5976 | 10.0 | 500 | 10.5656 | 0.464 | 0.6416 | 0.5044 | 0.0536 | 0.0797 | 0.4902 | 0.5143 | 0.6661 | 0.7398 | 0.35 | 0.4801 | 0.7745 | 0.6777 | 0.8596 | 0.4888 | 0.7716 | 0.1536 | 0.6286 | -1.0 | -1.0 | 0.2042 | 0.6056 | 0.3921 | 0.7071 | 0.8673 | 0.8667 |
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  ### Framework versions
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- - Transformers 4.52.4
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- - Pytorch 2.7.0+cu126
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- - Datasets 3.6.0
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- - Tokenizers 0.21.1
 
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  tags:
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  - generated_from_trainer
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  model-index:
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+ - name: learn_hf-rt-detrv2-finetuned-on-trashify-dataset-video
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  results: []
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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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+ # learn_hf-rt-detrv2-finetuned-on-trashify-dataset-video
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  This model is a fine-tuned version of [PekingU/rtdetr_v2_r50vd](https://huggingface.co/PekingU/rtdetr_v2_r50vd) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 10.1612
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+ - Map: 0.4478
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+ - Map 50: 0.5864
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+ - Map 75: 0.5096
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+ - Map Small: 0.0
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+ - Map Medium: 0.2891
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+ - Map Large: 0.4581
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+ - Mar 1: 0.5121
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+ - Mar 10: 0.7092
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+ - Mar 100: 0.7613
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+ - Mar Small: 0.0
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+ - Mar Medium: 0.5975
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+ - Mar Large: 0.7815
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+ - Map Bin: 0.746
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+ - Mar Bin: 0.9187
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+ - Map Hand: 0.5961
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+ - Mar Hand: 0.8136
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+ - Map Not Bin: 0.0561
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+ - Mar Not Bin: 0.5727
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+ - Map Not Hand: 0.0185
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+ - Mar Not Hand: 0.6333
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+ - Map Not Trash: 0.2151
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+ - Mar Not Trash: 0.6222
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+ - Map Trash: 0.6585
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+ - Mar Trash: 0.8397
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+ - Map Trash Arm: 0.8444
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+ - Mar Trash Arm: 0.9286
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  ## Model description
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  ### Training results
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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 Bin | Mar Bin | Map Hand | Mar Hand | Map Not Bin | Mar Not Bin | Map Not Hand | Mar Not Hand | Map Not Trash | Mar Not Trash | Map Trash | Mar Trash | Map Trash Arm | Mar Trash Arm |
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+ |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:----------:|:---------:|:------:|:------:|:-------:|:---------:|:----------:|:---------:|:-------:|:-------:|:--------:|:--------:|:-----------:|:-----------:|:------------:|:------------:|:-------------:|:-------------:|:---------:|:---------:|:-------------:|:-------------:|
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+ | 90.2652 | 1.0 | 50 | 22.7169 | 0.2343 | 0.342 | 0.2447 | 0.0 | 0.0133 | 0.2432 | 0.3225 | 0.502 | 0.5748 | 0.0 | 0.0977 | 0.628 | 0.5467 | 0.8326 | 0.4655 | 0.65 | 0.007 | 0.45 | -1.0 | -1.0 | 0.0117 | 0.3264 | 0.3706 | 0.623 | 0.0044 | 0.5667 |
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+ | 26.5507 | 2.0 | 100 | 13.5049 | 0.4103 | 0.5773 | 0.4496 | 0.02 | 0.1152 | 0.4293 | 0.4729 | 0.6547 | 0.7171 | 0.1 | 0.3898 | 0.7515 | 0.6658 | 0.8965 | 0.5505 | 0.7667 | 0.008 | 0.5071 | -1.0 | -1.0 | 0.1584 | 0.5111 | 0.6138 | 0.7876 | 0.4657 | 0.8333 |
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+ | 19.0339 | 3.0 | 150 | 11.7506 | 0.4485 | 0.6168 | 0.528 | 0.0714 | 0.2235 | 0.4651 | 0.5086 | 0.7004 | 0.7429 | 0.25 | 0.5403 | 0.7789 | 0.6937 | 0.8894 | 0.596 | 0.7931 | 0.0112 | 0.55 | -1.0 | -1.0 | 0.1558 | 0.5931 | 0.6348 | 0.7982 | 0.5993 | 0.8333 |
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+ | 16.4727 | 4.0 | 200 | 11.0906 | 0.5126 | 0.6896 | 0.5739 | 0.0 | 0.2155 | 0.5353 | 0.5473 | 0.7081 | 0.7555 | 0.0 | 0.4216 | 0.798 | 0.7116 | 0.8851 | 0.6232 | 0.7922 | 0.0478 | 0.55 | -1.0 | -1.0 | 0.2404 | 0.5819 | 0.6315 | 0.7903 | 0.8211 | 0.9333 |
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+ | 15.0827 | 5.0 | 250 | 10.7144 | 0.4955 | 0.6776 | 0.5712 | 0.125 | 0.225 | 0.518 | 0.5428 | 0.695 | 0.7541 | 0.25 | 0.4699 | 0.7957 | 0.7618 | 0.9113 | 0.5424 | 0.7735 | 0.0344 | 0.5357 | -1.0 | -1.0 | 0.248 | 0.5986 | 0.6267 | 0.8053 | 0.7599 | 0.9 |
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+ | 13.9634 | 6.0 | 300 | 10.6771 | 0.5377 | 0.7197 | 0.5907 | 0.2 | 0.3086 | 0.567 | 0.571 | 0.737 | 0.7894 | 0.2 | 0.5352 | 0.8348 | 0.7489 | 0.9121 | 0.5976 | 0.7951 | 0.1615 | 0.7214 | -1.0 | -1.0 | 0.2387 | 0.6 | 0.6643 | 0.808 | 0.8148 | 0.9 |
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+ | 13.0714 | 7.0 | 350 | 10.4076 | 0.5525 | 0.7296 | 0.6065 | 0.2 | 0.1863 | 0.5876 | 0.5696 | 0.7384 | 0.781 | 0.2 | 0.3295 | 0.8492 | 0.7707 | 0.9078 | 0.629 | 0.8127 | 0.1764 | 0.5929 | -1.0 | -1.0 | 0.2363 | 0.5889 | 0.657 | 0.8168 | 0.8456 | 0.9667 |
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+ | 12.405 | 8.0 | 400 | 10.2652 | 0.5346 | 0.7063 | 0.6085 | 0.3 | 0.2124 | 0.5697 | 0.55 | 0.7165 | 0.7691 | 0.3 | 0.3716 | 0.8306 | 0.7666 | 0.9028 | 0.5832 | 0.8118 | 0.1874 | 0.5786 | -1.0 | -1.0 | 0.2255 | 0.6153 | 0.644 | 0.8062 | 0.8007 | 0.9 |
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+ | 11.7512 | 9.0 | 450 | 10.0407 | 0.5506 | 0.7358 | 0.6293 | 0.3 | 0.2311 | 0.5877 | 0.5614 | 0.7456 | 0.7755 | 0.3 | 0.4398 | 0.8337 | 0.7602 | 0.9142 | 0.6356 | 0.8029 | 0.2287 | 0.5857 | -1.0 | -1.0 | 0.2414 | 0.6306 | 0.6674 | 0.8195 | 0.7705 | 0.9 |
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+ | 11.3543 | 10.0 | 500 | 10.0798 | 0.5401 | 0.7284 | 0.6267 | 0.3 | 0.2092 | 0.5756 | 0.5473 | 0.7485 | 0.7801 | 0.3 | 0.3767 | 0.8405 | 0.7629 | 0.905 | 0.6323 | 0.8059 | 0.2095 | 0.5857 | -1.0 | -1.0 | 0.2192 | 0.6278 | 0.6597 | 0.823 | 0.7569 | 0.9333 |
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  ### Framework versions
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+ - Transformers 4.53.1
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+ - Pytorch 2.6.0+cu124
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+ - Datasets 4.0.0
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+ - Tokenizers 0.21.2
config.json CHANGED
@@ -125,7 +125,7 @@
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  "num_queries": 300,
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  "positional_encoding_temperature": 10000,
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  "torch_dtype": "float32",
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- "transformers_version": "4.52.4",
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  "use_focal_loss": true,
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  "use_pretrained_backbone": false,
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  "use_timm_backbone": false,
 
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  "num_queries": 300,
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  "positional_encoding_temperature": 10000,
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  "torch_dtype": "float32",
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+ "transformers_version": "4.53.1",
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  "use_focal_loss": true,
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  "use_pretrained_backbone": false,
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  "use_timm_backbone": false,
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