76807fae71
* YOLOv5 forward compatibility update * add data dir * ci test yolov3 * update build_targets() * update build_targets() * update build_targets() * update yolov3-spp.yaml * add yolov3-tiny.yaml * add yolov3-tiny.yaml * Update yolov3-tiny.yaml * thop bug fix * Detection() device bug fix * Use torchvision.ops.nms() * Remove redundant download mirror * CI tests with yolov3-tiny * Update README.md * Synch train and test iou_thresh * update requirements.txt * Cat apriori autolabels * Confusion matrix * Autosplit * Autosplit * Update README.md * AP no plot * Update caching * Update caching * Caching bug fix * --image-weights bug fix * datasets bug fix * mosaic plots bug fix * plot_study * boxes.max() * boxes.max() * boxes.max() * boxes.max() * boxes.max() * boxes.max() * update * Update README * Update README * Update README.md * Update README.md * results png * Update README * Targets scaling bug fix * update plot_study * update plot_study * update plot_study * update plot_study * Targets scaling bug fix * Finish Readme.md * Finish Readme.md * Finish Readme.md * Update README.md * Creado con Colaboratory
39 lines
846 B
YAML
39 lines
846 B
YAML
# Hyperparameters for VOC finetuning
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# python train.py --batch 64 --weights yolov5m.pt --data voc.yaml --img 512 --epochs 50
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# See tutorials for hyperparameter evolution https://github.com/ultralytics/yolov5#tutorials
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# Hyperparameter Evolution Results
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# Generations: 306
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# P R mAP.5 mAP.5:.95 box obj cls
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# Metrics: 0.6 0.936 0.896 0.684 0.0115 0.00805 0.00146
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lr0: 0.0032
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lrf: 0.12
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momentum: 0.843
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weight_decay: 0.00036
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warmup_epochs: 2.0
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warmup_momentum: 0.5
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warmup_bias_lr: 0.05
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box: 0.0296
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cls: 0.243
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cls_pw: 0.631
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obj: 0.301
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obj_pw: 0.911
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iou_t: 0.2
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anchor_t: 2.91
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# anchors: 3.63
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fl_gamma: 0.0
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hsv_h: 0.0138
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hsv_s: 0.664
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hsv_v: 0.464
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degrees: 0.373
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translate: 0.245
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scale: 0.898
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shear: 0.602
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perspective: 0.0
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flipud: 0.00856
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fliplr: 0.5
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mosaic: 1.0
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mixup: 0.243
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