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179 lines
4.9 KiB
179 lines
4.9 KiB
# Instagram ResNeXt WSL
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A **ResNeXt** repeats a [building block](https://paperswithcode.com/method/resnext-block) that aggregates a set of transformations with the same topology. Compared to a [ResNet](https://paperswithcode.com/method/resnet), it exposes a new dimension, *cardinality* (the size of the set of transformations) $C$, as an essential factor in addition to the dimensions of depth and width.
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This model was trained on billions of Instagram images using thousands of distinct hashtags as labels exhibit excellent transfer learning performance.
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Please note the CC-BY-NC 4.0 license on theses weights, non-commercial use only.
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{% include 'code_snippets.md' %}
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## How do I train this model?
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You can follow the [timm recipe scripts](https://rwightman.github.io/pytorch-image-models/scripts/) for training a new model afresh.
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## Citation
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```BibTeX
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@misc{mahajan2018exploring,
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title={Exploring the Limits of Weakly Supervised Pretraining},
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author={Dhruv Mahajan and Ross Girshick and Vignesh Ramanathan and Kaiming He and Manohar Paluri and Yixuan Li and Ashwin Bharambe and Laurens van der Maaten},
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year={2018},
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eprint={1805.00932},
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archivePrefix={arXiv},
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primaryClass={cs.CV}
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}
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```
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<!--
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Models:
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- Name: ig_resnext101_32x32d
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Metadata:
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FLOPs: 112225170432
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Epochs: 100
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Batch Size: 8064
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Training Data:
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- IG-3.5B-17k
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- ImageNet
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Training Techniques:
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- Nesterov Accelerated Gradient
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- Weight Decay
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Training Resources: 336x GPUs
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Architecture:
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- 1x1 Convolution
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- Batch Normalization
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- Convolution
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- Global Average Pooling
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- Grouped Convolution
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- Max Pooling
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- ReLU
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- ResNeXt Block
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- Residual Connection
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- Softmax
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File Size: 1876573776
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Tasks:
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- Image Classification
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ID: ig_resnext101_32x32d
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Layers: 101
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Crop Pct: '0.875'
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Momentum: 0.9
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Image Size: '224'
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Weight Decay: 0.001
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Interpolation: bilinear
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Minibatch Size: 8064
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Code: https://github.com/rwightman/pytorch-image-models/blob/d8e69206be253892b2956341fea09fdebfaae4e3/timm/models/resnet.py#L885
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In Collection: IG ResNeXt
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- Name: ig_resnext101_32x16d
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Metadata:
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FLOPs: 46623691776
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Epochs: 100
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Batch Size: 8064
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Training Data:
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- IG-3.5B-17k
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- ImageNet
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Training Techniques:
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- Nesterov Accelerated Gradient
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- Weight Decay
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Training Resources: 336x GPUs
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Architecture:
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- 1x1 Convolution
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- Batch Normalization
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- Convolution
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- Global Average Pooling
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- Grouped Convolution
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- Max Pooling
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- ReLU
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- ResNeXt Block
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- Residual Connection
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- Softmax
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File Size: 777518664
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Tasks:
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- Image Classification
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ID: ig_resnext101_32x16d
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Layers: 101
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Crop Pct: '0.875'
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Momentum: 0.9
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Image Size: '224'
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Weight Decay: 0.001
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Interpolation: bilinear
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Code: https://github.com/rwightman/pytorch-image-models/blob/d8e69206be253892b2956341fea09fdebfaae4e3/timm/models/resnet.py#L874
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In Collection: IG ResNeXt
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- Name: ig_resnext101_32x48d
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Metadata:
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FLOPs: 197446554624
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Epochs: 100
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Batch Size: 8064
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Training Data:
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- IG-3.5B-17k
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- ImageNet
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Training Techniques:
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- Nesterov Accelerated Gradient
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- Weight Decay
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Training Resources: 336x GPUs
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Architecture:
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- 1x1 Convolution
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- Batch Normalization
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- Convolution
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- Global Average Pooling
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- Grouped Convolution
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- Max Pooling
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- ReLU
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- ResNeXt Block
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- Residual Connection
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- Softmax
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File Size: 3317136976
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Tasks:
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- Image Classification
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ID: ig_resnext101_32x48d
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Layers: 101
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Crop Pct: '0.875'
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Momentum: 0.9
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Image Size: '224'
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Weight Decay: 0.001
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Interpolation: bilinear
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Code: https://github.com/rwightman/pytorch-image-models/blob/d8e69206be253892b2956341fea09fdebfaae4e3/timm/models/resnet.py#L896
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In Collection: IG ResNeXt
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- Name: ig_resnext101_32x8d
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Metadata:
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FLOPs: 21180417024
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Epochs: 100
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Batch Size: 8064
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Training Data:
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- IG-3.5B-17k
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- ImageNet
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Training Techniques:
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- Nesterov Accelerated Gradient
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- Weight Decay
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Training Resources: 336x GPUs
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Architecture:
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- 1x1 Convolution
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- Batch Normalization
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- Convolution
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- Global Average Pooling
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- Grouped Convolution
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- Max Pooling
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- ReLU
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- ResNeXt Block
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- Residual Connection
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- Softmax
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File Size: 356056638
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Tasks:
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- Image Classification
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ID: ig_resnext101_32x8d
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Layers: 101
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Crop Pct: '0.875'
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Momentum: 0.9
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Image Size: '224'
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Weight Decay: 0.001
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Interpolation: bilinear
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Code: https://github.com/rwightman/pytorch-image-models/blob/d8e69206be253892b2956341fea09fdebfaae4e3/timm/models/resnet.py#L863
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In Collection: IG ResNeXt
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Collections:
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- Name: IG ResNeXt
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Paper:
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title: Exploring the Limits of Weakly Supervised Pretraining
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url: https://paperswithcode.com//paper/exploring-the-limits-of-weakly-supervised
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type: model-index
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Type: model-index
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-->
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