metafile.yml 1.5 KB

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  1. Collections:
  2. - Name: MoCoV2
  3. Metadata:
  4. Training Data: ImageNet-1k
  5. Training Techniques:
  6. - SGD with Momentum
  7. - Weight Decay
  8. Training Resources: 8x V100 GPUs
  9. Architecture:
  10. - ResNet
  11. - MoCo
  12. Paper:
  13. Title: Improved Baselines with Momentum Contrastive Learning
  14. URL: https://arxiv.org/abs/2003.04297
  15. README: configs/mocov2/README.md
  16. Models:
  17. - Name: mocov2_resnet50_8xb32-coslr-200e_in1k
  18. Metadata:
  19. Epochs: 200
  20. Batch Size: 256
  21. FLOPs: 4109364224
  22. Parameters: 55933312
  23. Training Data: ImageNet-1k
  24. In Collection: MoCoV2
  25. Results: null
  26. Weights: https://download.openmmlab.com/mmselfsup/1.x/mocov2/mocov2_resnet50_8xb32-coslr-200e_in1k/mocov2_resnet50_8xb32-coslr-200e_in1k_20220825-b6d23c86.pth
  27. Config: configs/mocov2/mocov2_resnet50_8xb32-coslr-200e_in1k.py
  28. Downstream:
  29. - resnet50_mocov2-pre_8xb32-linear-steplr-100e_in1k
  30. - Name: resnet50_mocov2-pre_8xb32-linear-steplr-100e_in1k
  31. Metadata:
  32. Epochs: 100
  33. Batch Size: 256
  34. FLOPs: 4109464576
  35. Parameters: 25557032
  36. Training Data: ImageNet-1k
  37. In Collection: MoCoV2
  38. Results:
  39. - Task: Image Classification
  40. Dataset: ImageNet-1k
  41. Metrics:
  42. Top 1 Accuracy: 67.5
  43. Weights: https://download.openmmlab.com/mmselfsup/1.x/mocov2/mocov2_resnet50_8xb32-coslr-200e_in1k/resnet50_linear-8xb32-steplr-100e_in1k/resnet50_linear-8xb32-steplr-100e_in1k_20220825-994c4128.pth
  44. Config: configs/mocov2/benchmarks/resnet50_8xb32-linear-steplr-100e_in1k.py