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red-squirrel-detector

Object Detection
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d_fine
vision
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metadata 
library_name: transformers
license: apache-2.0
base_model: ustc-community/dfine-small-coco
tags:
  - object-detection
  - vision
  - generated_from_trainer
model-index:
  - name: red-squirrel-detector
    results: []

red-squirrel-detector

This model is a fine-tuned version of ustc-community/dfine-small-coco on the davanstrien/squirrel-cam-labeled dataset. It achieves the following results on the evaluation set:

  • Loss: 0.7587
  • Map: 0.8614
  • Map 50: 0.9087
  • Map 75: 0.8839
  • Map Small: 0.0
  • Map Medium: 0.63
  • Map Large: 0.8901
  • Mar 1: 0.7528
  • Mar 10: 0.8876
  • Mar 100: 0.9441
  • Mar Small: 0.0
  • Mar Medium: 0.7769
  • Mar Large: 0.9653
  • Map Class 0: 0.8614
  • Mar 100 Class 0: 0.9441

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
  • num_epochs: 30.0

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 Class 0 Mar 100 Class 0
No log 1.0 91 2.3672 0.1766 0.23 0.1862 0.0 0.0031 0.1989 0.3422 0.5248 0.6224 0.0 0.3462 0.651 0.1766 0.6224
No log 2.0 182 1.0651 0.7244 0.8127 0.7856 0.0 0.4261 0.7538 0.6901 0.7888 0.8596 0.0 0.6385 0.885 0.7244 0.8596
No log 3.0 273 0.8899 0.7577 0.8321 0.7881 0.0 0.4732 0.7986 0.7137 0.8311 0.8863 0.0 0.6769 0.9109 0.7577 0.8863
No log 4.0 364 0.8310 0.7773 0.8432 0.8045 0.0 0.586 0.814 0.7124 0.841 0.8894 0.0 0.7 0.9122 0.7773 0.8894
No log 5.0 455 0.8333 0.7792 0.8513 0.8058 0.0 0.6129 0.8197 0.718 0.8317 0.9031 0.0 0.7077 0.9265 0.7792 0.9031
27.3840 6.0 546 0.8361 0.8008 0.8684 0.8296 0.0 0.5788 0.8348 0.723 0.8609 0.9124 0.0 0.7077 0.9367 0.8008 0.9124
27.3840 7.0 637 0.8078 0.8 0.8587 0.8191 0.0 0.5968 0.8365 0.7224 0.8739 0.9211 0.0 0.7308 0.9442 0.8 0.9211
27.3840 8.0 728 0.8232 0.8173 0.8877 0.837 0.0 0.6199 0.8476 0.7205 0.8677 0.9161 0.0 0.7 0.9415 0.8173 0.9161
27.3840 9.0 819 0.7746 0.8268 0.8863 0.8541 0.0 0.6029 0.8577 0.7211 0.8702 0.9224 0.0 0.6692 0.951 0.8268 0.9224
27.3840 10.0 910 0.8223 0.8324 0.8875 0.8682 0.0 0.6198 0.8586 0.7311 0.8801 0.9193 0.0 0.6923 0.9456 0.8324 0.9193
9.0922 11.0 1001 0.7678 0.8327 0.8851 0.8689 0.0 0.5991 0.8634 0.7422 0.8671 0.9255 0.0 0.6846 0.9531 0.8327 0.9255
9.0922 12.0 1092 0.7850 0.8328 0.8888 0.8545 0.0 0.6134 0.8635 0.7366 0.8752 0.9335 0.0 0.7231 0.9585 0.8328 0.9335
9.0922 13.0 1183 0.8330 0.8294 0.8882 0.8485 0.0 0.583 0.8585 0.7416 0.8689 0.9267 0.0 0.7308 0.9503 0.8294 0.9267
9.0922 14.0 1274 0.7800 0.8399 0.8977 0.8761 0.0056 0.5989 0.87 0.741 0.8758 0.9348 0.6 0.7692 0.9517 0.8399 0.9348
9.0922 15.0 1365 0.7595 0.8437 0.8993 0.8771 0.0061 0.6092 0.8731 0.7509 0.8925 0.9466 0.6 0.7846 0.9633 0.8437 0.9466
9.0922 16.0 1456 0.7758 0.843 0.9059 0.8657 0.0 0.6186 0.8713 0.7472 0.8783 0.9385 0.0 0.7308 0.9633 0.843 0.9385
8.3234 17.0 1547 0.8078 0.844 0.9017 0.8816 0.009 0.6091 0.8754 0.7453 0.8957 0.9366 0.6 0.7077 0.9592 0.844 0.9366
8.3234 18.0 1638 0.7719 0.8479 0.9069 0.8728 0.0 0.6086 0.8785 0.7522 0.8882 0.9273 0.0 0.7077 0.9531 0.8479 0.9273
8.3234 19.0 1729 0.7562 0.8552 0.9105 0.8779 0.0 0.6193 0.8853 0.7509 0.8882 0.9323 0.0 0.7077 0.9585 0.8552 0.9323
8.3234 20.0 1820 0.8166 0.8478 0.9076 0.8774 0.0 0.6428 0.8765 0.7528 0.8988 0.9379 0.0 0.7231 0.9633 0.8478 0.9379
8.3234 21.0 1911 0.7616 0.8519 0.9053 0.8843 0.0 0.6332 0.8818 0.7578 0.8919 0.9385 0.0 0.7154 0.9646 0.8519 0.9385
7.9949 22.0 2002 0.7445 0.857 0.9102 0.8872 0.0 0.6327 0.8856 0.7497 0.8839 0.9354 0.0 0.7231 0.9605 0.857 0.9354
7.9949 23.0 2093 0.7569 0.85 0.9003 0.8792 0.0 0.6308 0.8802 0.7516 0.9019 0.9366 0.0 0.7154 0.9626 0.85 0.9366
7.9949 24.0 2184 0.7550 0.862 0.9093 0.8837 0.0 0.6277 0.8917 0.7516 0.8882 0.9441 0.0 0.7769 0.9653 0.862 0.9441
7.9949 25.0 2275 0.7435 0.8561 0.9053 0.8875 0.0055 0.6371 0.885 0.7559 0.8981 0.9478 0.7 0.7923 0.9633 0.8561 0.9478
7.9949 26.0 2366 0.7752 0.8441 0.8961 0.8669 0.0 0.6392 0.8717 0.7553 0.8857 0.9398 0.0 0.7923 0.9592 0.8441 0.9398
7.9949 27.0 2457 0.7505 0.8505 0.8966 0.8745 0.0 0.6337 0.88 0.7565 0.8857 0.9441 0.0 0.7923 0.9639 0.8505 0.9441
7.6820 28.0 2548 0.7449 0.8533 0.9012 0.8801 0.0 0.627 0.8826 0.7553 0.8901 0.9416 0.0 0.7769 0.9626 0.8533 0.9416
7.6820 29.0 2639 0.7330 0.8577 0.9052 0.8842 0.0076 0.6278 0.8874 0.7571 0.8975 0.9497 0.8 0.7769 0.966 0.8577 0.9497
7.6820 30.0 2730 0.7412 0.8559 0.9016 0.8852 0.0 0.6332 0.8848 0.7571 0.8957 0.9385 0.0 0.7231 0.9639 0.8559 0.9385

Framework versions

  • Transformers 5.4.0
  • Pytorch 2.11.0+cu130
  • Datasets 4.8.4
  • Tokenizers 0.22.2