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jparedesDS
/
valorant-yolo11m

Object Detection
TensorBoard
yolo11
valorant
object
detection
Model card Files Metrics Community
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  1. F1_curve.png +0 -0
  2. PR_curve.png +0 -0
  3. P_curve.png +0 -0
  4. R_curve.png +0 -0
  5. args.yaml +107 -0
  6. confusion_matrix.png +0 -0
  7. confusion_matrix_normalized.png +0 -0
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  9. labels.jpg +0 -0
  10. labels_correlogram.jpg +0 -0
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  13. train_batch0.jpg +0 -0
  14. train_batch1.jpg +0 -0
  15. train_batch2.jpg +0 -0
  16. train_batch22610.jpg +0 -0
  17. train_batch22611.jpg +0 -0
  18. train_batch22612.jpg +0 -0
  19. val_batch0_labels.jpg +0 -0
  20. val_batch0_pred.jpg +0 -0
  21. val_batch1_labels.jpg +0 -0
  22. val_batch1_pred.jpg +0 -0
  23. val_batch2_labels.jpg +0 -0
  24. val_batch2_pred.jpg +0 -0
  25. vlr-yolo11m.pt +3 -0
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+ task: detect
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+ mode: train
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+ model: yolo11m.pt
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+ data: /content/drive/MyDrive/OBJECT DETECTION/00. Datasets/vlr_v2/data.yaml
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+ epochs: 200
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+ time: null
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+ patience: 100
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+ batch: -1
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+ imgsz: 640
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+ save: true
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+ save_period: 50
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+ cache: false
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+ device: null
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+ workers: 8
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+ project: null
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+ name: train
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+ exist_ok: false
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+ pretrained: true
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+ optimizer: auto
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+ verbose: true
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+ seed: 0
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+ deterministic: true
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+ single_cls: false
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+ rect: false
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+ close_mosaic: 10
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+ overlap_mask: true
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+ mask_ratio: 4
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+ val: true
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+ split: val
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+ save_hybrid: false
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+ conf: null
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+ iou: 0.7
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+ max_det: 300
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+ half: false
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+ dnn: false
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+ plots: true
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+ source: null
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+ vid_stride: 1
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+ stream_buffer: false
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+ visualize: false
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+ augment: false
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+ agnostic_nms: false
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+ classes: null
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+ retina_masks: false
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+ embed: null
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+ show: false
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+ save_frames: false
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+ save_txt: false
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+ save_crop: false
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+ show_labels: true
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+ format: torchscript
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+ optimize: false
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+ int8: false
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+ dynamic: false
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+ simplify: true
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+ opset: null
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+ workspace: 4
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+ nms: false
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+ lr0: 0.01
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+ momentum: 0.937
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+ weight_decay: 0.0005
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+ copy_paste_mode: flip
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+ auto_augment: randaugment
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+ erasing: 0.4
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+ crop_fraction: 1.0
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+ cfg: null
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+ tracker: botsort.yaml
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+ save_dir: runs/detect/train
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+ epoch, train/box_loss, train/cls_loss, train/dfl_loss, metrics/precision(B), metrics/recall(B), metrics/mAP50(B), metrics/mAP50-95(B), val/box_loss, val/cls_loss, val/dfl_loss, lr/pg0, lr/pg1, lr/pg2
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94
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100
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150
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158
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170
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185
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186
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187
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188
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