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256 lines
6.4 KiB
256 lines
6.4 KiB
3 years ago
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# Big Transfer (BiT)
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3 years ago
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**Big Transfer (BiT)** is a type of pretraining recipe that pre-trains on a large supervised source dataset, and fine-tunes the weights on the target task. Models are trained on the JFT-300M dataset. The finetuned models contained in this collection are finetuned on ImageNet.
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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{kolesnikov2020big,
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title={Big Transfer (BiT): General Visual Representation Learning},
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author={Alexander Kolesnikov and Lucas Beyer and Xiaohua Zhai and Joan Puigcerver and Jessica Yung and Sylvain Gelly and Neil Houlsby},
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year={2020},
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eprint={1912.11370},
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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: resnetv2_152x4_bitm
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Metadata:
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Training Data:
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- ImageNet
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- JFT-300M
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Training Techniques:
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- Mixup
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- SGD with Momentum
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- Weight Decay
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Training Resources: Cloud TPUv3-512
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Architecture:
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- 1x1 Convolution
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- Bottleneck Residual Block
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- Convolution
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- Global Average Pooling
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- Group Normalization
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- Max Pooling
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- ReLU
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- Residual Block
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- Residual Connection
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- Softmax
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- Weight Standardization
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File Size: 3746270104
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Tasks:
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- Image Classification
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Training Time: ''
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ID: resnetv2_152x4_bitm
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Crop Pct: '1.0'
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Image Size: '480'
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Interpolation: bilinear
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Code: https://github.com/rwightman/pytorch-image-models/blob/b9843f954b0457af2db4f9dea41a8538f51f5d78/timm/models/resnetv2.py#L465
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Config: ''
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In Collection: Big Transfer
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- Name: resnetv2_152x2_bitm
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Metadata:
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Training Data:
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- ImageNet
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- JFT-300M
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Training Techniques:
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- Mixup
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- SGD with Momentum
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- Weight Decay
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Training Resources: ''
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Architecture:
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- 1x1 Convolution
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- Bottleneck Residual Block
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- Convolution
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- Global Average Pooling
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- Group Normalization
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- Max Pooling
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- ReLU
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- Residual Block
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- Residual Connection
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- Softmax
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- Weight Standardization
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File Size: 945476668
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Tasks:
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- Image Classification
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Training Time: ''
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ID: resnetv2_152x2_bitm
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Crop Pct: '1.0'
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Image Size: '480'
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Interpolation: bilinear
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Code: https://github.com/rwightman/pytorch-image-models/blob/b9843f954b0457af2db4f9dea41a8538f51f5d78/timm/models/resnetv2.py#L458
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Config: ''
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In Collection: Big Transfer
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- Name: resnetv2_50x1_bitm
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Metadata:
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Epochs: 90
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Batch Size: 4096
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Training Data:
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- ImageNet
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- JFT-300M
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Training Techniques:
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- Mixup
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- SGD with Momentum
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- Weight Decay
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Training Resources: Cloud TPUv3-512
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Architecture:
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- 1x1 Convolution
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- Bottleneck Residual Block
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- Convolution
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- Global Average Pooling
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- Group Normalization
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- Max Pooling
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- ReLU
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- Residual Block
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- Residual Connection
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- Softmax
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- Weight Standardization
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File Size: 102242668
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Tasks:
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- Image Classification
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Training Time: ''
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ID: resnetv2_50x1_bitm
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LR: 0.03
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Layers: 50
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Crop Pct: '1.0'
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Momentum: 0.9
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Image Size: '480'
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Weight Decay: 0.0001
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Interpolation: bilinear
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Code: https://github.com/rwightman/pytorch-image-models/blob/b9843f954b0457af2db4f9dea41a8538f51f5d78/timm/models/resnetv2.py#L430
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Config: ''
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In Collection: Big Transfer
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- Name: resnetv2_101x3_bitm
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Metadata:
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Epochs: 90
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Batch Size: 4096
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Training Data:
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- ImageNet
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- JFT-300M
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Training Techniques:
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- Mixup
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- SGD with Momentum
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- Weight Decay
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Training Resources: Cloud TPUv3-512
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Architecture:
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- 1x1 Convolution
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- Bottleneck Residual Block
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- Convolution
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- Global Average Pooling
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- Group Normalization
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- Max Pooling
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- ReLU
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- Residual Block
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- Residual Connection
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- Softmax
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- Weight Standardization
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File Size: 1551830100
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Tasks:
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- Image Classification
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Training Time: ''
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ID: resnetv2_101x3_bitm
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LR: 0.03
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Layers: 101
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Crop Pct: '1.0'
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Momentum: 0.9
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Image Size: '480'
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Weight Decay: 0.0001
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Interpolation: bilinear
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Code: https://github.com/rwightman/pytorch-image-models/blob/b9843f954b0457af2db4f9dea41a8538f51f5d78/timm/models/resnetv2.py#L451
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Config: ''
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In Collection: Big Transfer
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- Name: resnetv2_50x3_bitm
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Metadata:
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Epochs: 90
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Batch Size: 4096
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Training Data:
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- ImageNet
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- JFT-300M
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Training Techniques:
|
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|
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- Mixup
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|
|
- SGD with Momentum
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|
|
- Weight Decay
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Training Resources: Cloud TPUv3-512
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|
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Architecture:
|
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|
|
- 1x1 Convolution
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|
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- Bottleneck Residual Block
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|
|
- Convolution
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|
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- Global Average Pooling
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|
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- Group Normalization
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|
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- Max Pooling
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- ReLU
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- Residual Block
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- Residual Connection
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- Softmax
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- Weight Standardization
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File Size: 869321580
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Tasks:
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- Image Classification
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Training Time: ''
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ID: resnetv2_50x3_bitm
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LR: 0.03
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Layers: 50
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Crop Pct: '1.0'
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Momentum: 0.9
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Image Size: '480'
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Weight Decay: 0.0001
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Interpolation: bilinear
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Code: https://github.com/rwightman/pytorch-image-models/blob/b9843f954b0457af2db4f9dea41a8538f51f5d78/timm/models/resnetv2.py#L437
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Config: ''
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In Collection: Big Transfer
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- Name: resnetv2_101x1_bitm
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Metadata:
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Epochs: 90
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Batch Size: 4096
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Training Data:
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- ImageNet
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- JFT-300M
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Training Techniques:
|
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- Mixup
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- SGD with Momentum
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- Weight Decay
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Training Resources: Cloud TPUv3-512
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Architecture:
|
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- 1x1 Convolution
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- Bottleneck Residual Block
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- Convolution
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- Global Average Pooling
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- Group Normalization
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- Max Pooling
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- ReLU
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- Residual Block
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- Residual Connection
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- Softmax
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- Weight Standardization
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File Size: 178256468
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Tasks:
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- Image Classification
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Training Time: ''
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ID: resnetv2_101x1_bitm
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LR: 0.03
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Layers: 101
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Crop Pct: '1.0'
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Momentum: 0.9
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Image Size: '480'
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Weight Decay: 0.0001
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Interpolation: bilinear
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Code: https://github.com/rwightman/pytorch-image-models/blob/b9843f954b0457af2db4f9dea41a8538f51f5d78/timm/models/resnetv2.py#L444
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Config: ''
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In Collection: Big Transfer
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Collections:
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- Name: Big Transfer
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Paper:
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title: 'Big Transfer (BiT): General Visual Representation Learning'
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3 years ago
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url: https://paperswithcode.com//paper/large-scale-learning-of-general-visual
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3 years ago
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type: model-index
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Type: model-index
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-->
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