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457 lines
12 KiB
457 lines
12 KiB
# Noisy Student (EfficientNet)
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**Noisy Student Training** is a semi-supervised learning approach. It extends the idea of self-training
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and distillation with the use of equal-or-larger student models and noise added to the student during learning. It has three main steps:
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1. train a teacher model on labeled images
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2. use the teacher to generate pseudo labels on unlabeled images
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3. train a student model on the combination of labeled images and pseudo labeled images.
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The algorithm is iterated a few times by treating the student as a teacher to relabel the unlabeled data and training a new student.
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Noisy Student Training seeks to improve on self-training and distillation in two ways. First, it makes the student larger than, or at least equal to, the teacher so the student can better learn from a larger dataset. Second, it adds noise to the student so the noised student is forced to learn harder from the pseudo labels. To noise the student, it uses input noise such as RandAugment data augmentation, and model noise such as dropout and stochastic depth during training.
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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{xie2020selftraining,
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title={Self-training with Noisy Student improves ImageNet classification},
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author={Qizhe Xie and Minh-Thang Luong and Eduard Hovy and Quoc V. Le},
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year={2020},
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eprint={1911.04252},
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archivePrefix={arXiv},
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primaryClass={cs.LG}
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}
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```
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<!--
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Models:
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- Name: tf_efficientnet_b3_ns
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Metadata:
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FLOPs: 2275247568
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Epochs: 700
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Batch Size: 2048
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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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- AutoAugment
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- FixRes
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- Label Smoothing
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- Noisy Student
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- RMSProp
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- RandAugment
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- Weight Decay
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Training Resources: Cloud TPU v3 Pod
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Architecture:
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- 1x1 Convolution
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- Average Pooling
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- Batch Normalization
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- Convolution
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- Dense Connections
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- Dropout
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- Inverted Residual Block
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- Squeeze-and-Excitation Block
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- Swish
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File Size: 49385734
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Tasks:
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- Image Classification
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Training Time: ''
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ID: tf_efficientnet_b3_ns
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LR: 0.128
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Dropout: 0.5
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Crop Pct: '0.904'
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Momentum: 0.9
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Image Size: '300'
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Weight Decay: 1.0e-05
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Interpolation: bicubic
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RMSProp Decay: 0.9
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Label Smoothing: 0.1
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BatchNorm Momentum: 0.99
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Stochastic Depth Survival: 0.8
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Code: https://github.com/rwightman/pytorch-image-models/blob/9a25fdf3ad0414b4d66da443fe60ae0aa14edc84/timm/models/efficientnet.py#L1457
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Config: ''
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In Collection: Noisy Student
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- Name: tf_efficientnet_b1_ns
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Metadata:
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FLOPs: 883633200
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Epochs: 700
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Batch Size: 2048
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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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- AutoAugment
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- FixRes
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- Label Smoothing
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- Noisy Student
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- RMSProp
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- RandAugment
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- Weight Decay
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Training Resources: Cloud TPU v3 Pod
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Architecture:
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- 1x1 Convolution
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- Average Pooling
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- Batch Normalization
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- Convolution
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- Dense Connections
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- Dropout
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- Inverted Residual Block
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- Squeeze-and-Excitation Block
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- Swish
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File Size: 31516408
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Tasks:
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- Image Classification
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Training Time: ''
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ID: tf_efficientnet_b1_ns
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LR: 0.128
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Dropout: 0.5
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Crop Pct: '0.882'
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Momentum: 0.9
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Image Size: '240'
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Weight Decay: 1.0e-05
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Interpolation: bicubic
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RMSProp Decay: 0.9
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Label Smoothing: 0.1
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BatchNorm Momentum: 0.99
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Stochastic Depth Survival: 0.8
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Code: https://github.com/rwightman/pytorch-image-models/blob/9a25fdf3ad0414b4d66da443fe60ae0aa14edc84/timm/models/efficientnet.py#L1437
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Config: ''
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In Collection: Noisy Student
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- Name: tf_efficientnet_l2_ns
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Metadata:
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FLOPs: 611646113804
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Epochs: 350
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Batch Size: 2048
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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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- AutoAugment
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- FixRes
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- Label Smoothing
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- Noisy Student
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- RMSProp
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- RandAugment
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- Weight Decay
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Training Resources: Cloud TPU v3 Pod
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Architecture:
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- 1x1 Convolution
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- Average Pooling
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- Batch Normalization
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- Convolution
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- Dense Connections
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- Dropout
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- Inverted Residual Block
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- Squeeze-and-Excitation Block
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- Swish
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File Size: 1925950424
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Tasks:
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- Image Classification
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Training Time: 6 days
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ID: tf_efficientnet_l2_ns
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LR: 0.128
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Dropout: 0.5
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Crop Pct: '0.96'
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Momentum: 0.9
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Image Size: '800'
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Weight Decay: 1.0e-05
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Interpolation: bicubic
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RMSProp Decay: 0.9
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Label Smoothing: 0.1
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BatchNorm Momentum: 0.99
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Stochastic Depth Survival: 0.8
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Code: https://github.com/rwightman/pytorch-image-models/blob/9a25fdf3ad0414b4d66da443fe60ae0aa14edc84/timm/models/efficientnet.py#L1520
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Config: ''
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In Collection: Noisy Student
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- Name: tf_efficientnet_b0_ns
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Metadata:
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FLOPs: 488688572
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Epochs: 700
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Batch Size: 2048
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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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- AutoAugment
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- FixRes
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- Label Smoothing
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- Noisy Student
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- RMSProp
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- RandAugment
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- Weight Decay
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Training Resources: Cloud TPU v3 Pod
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Architecture:
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- 1x1 Convolution
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- Average Pooling
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- Batch Normalization
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- Convolution
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- Dense Connections
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- Dropout
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- Inverted Residual Block
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- Squeeze-and-Excitation Block
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- Swish
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File Size: 21386709
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Tasks:
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- Image Classification
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Training Time: ''
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ID: tf_efficientnet_b0_ns
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LR: 0.128
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Dropout: 0.5
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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: 1.0e-05
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Interpolation: bicubic
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RMSProp Decay: 0.9
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Label Smoothing: 0.1
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BatchNorm Momentum: 0.99
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Stochastic Depth Survival: 0.8
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Code: https://github.com/rwightman/pytorch-image-models/blob/9a25fdf3ad0414b4d66da443fe60ae0aa14edc84/timm/models/efficientnet.py#L1427
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Config: ''
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In Collection: Noisy Student
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- Name: tf_efficientnet_b2_ns
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Metadata:
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FLOPs: 1234321170
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Epochs: 700
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Batch Size: 2048
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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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- AutoAugment
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- FixRes
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- Label Smoothing
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- Noisy Student
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- RMSProp
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- RandAugment
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- Weight Decay
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Training Resources: Cloud TPU v3 Pod
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Architecture:
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- 1x1 Convolution
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- Average Pooling
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- Batch Normalization
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- Convolution
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- Dense Connections
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- Dropout
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- Inverted Residual Block
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- Squeeze-and-Excitation Block
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- Swish
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File Size: 36801803
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Tasks:
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- Image Classification
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Training Time: ''
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ID: tf_efficientnet_b2_ns
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LR: 0.128
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Dropout: 0.5
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Crop Pct: '0.89'
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Momentum: 0.9
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Image Size: '260'
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Weight Decay: 1.0e-05
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Interpolation: bicubic
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RMSProp Decay: 0.9
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Label Smoothing: 0.1
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BatchNorm Momentum: 0.99
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Stochastic Depth Survival: 0.8
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Code: https://github.com/rwightman/pytorch-image-models/blob/9a25fdf3ad0414b4d66da443fe60ae0aa14edc84/timm/models/efficientnet.py#L1447
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Config: ''
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In Collection: Noisy Student
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- Name: tf_efficientnet_b5_ns
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Metadata:
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FLOPs: 13176501888
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Epochs: 350
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Batch Size: 2048
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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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- AutoAugment
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- FixRes
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- Label Smoothing
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- Noisy Student
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- RMSProp
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- RandAugment
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- Weight Decay
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Training Resources: Cloud TPU v3 Pod
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Architecture:
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- 1x1 Convolution
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- Average Pooling
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- Batch Normalization
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- Convolution
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- Dense Connections
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- Dropout
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- Inverted Residual Block
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- Squeeze-and-Excitation Block
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- Swish
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File Size: 122404944
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Tasks:
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- Image Classification
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Training Time: ''
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ID: tf_efficientnet_b5_ns
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LR: 0.128
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Dropout: 0.5
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Crop Pct: '0.934'
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Momentum: 0.9
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Image Size: '456'
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Weight Decay: 1.0e-05
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Interpolation: bicubic
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RMSProp Decay: 0.9
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Label Smoothing: 0.1
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BatchNorm Momentum: 0.99
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Stochastic Depth Survival: 0.8
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Code: https://github.com/rwightman/pytorch-image-models/blob/9a25fdf3ad0414b4d66da443fe60ae0aa14edc84/timm/models/efficientnet.py#L1477
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Config: ''
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In Collection: Noisy Student
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- Name: tf_efficientnet_b6_ns
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Metadata:
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FLOPs: 24180518488
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Epochs: 350
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Batch Size: 2048
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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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- AutoAugment
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- FixRes
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- Label Smoothing
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- Noisy Student
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- RMSProp
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- RandAugment
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- Weight Decay
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Training Resources: Cloud TPU v3 Pod
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Architecture:
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- 1x1 Convolution
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- Average Pooling
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- Batch Normalization
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- Convolution
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- Dense Connections
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- Dropout
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- Inverted Residual Block
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- Squeeze-and-Excitation Block
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- Swish
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File Size: 173239537
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Tasks:
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- Image Classification
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Training Time: ''
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ID: tf_efficientnet_b6_ns
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LR: 0.128
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Dropout: 0.5
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Crop Pct: '0.942'
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Momentum: 0.9
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Image Size: '528'
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Weight Decay: 1.0e-05
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Interpolation: bicubic
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RMSProp Decay: 0.9
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Label Smoothing: 0.1
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BatchNorm Momentum: 0.99
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Stochastic Depth Survival: 0.8
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Code: https://github.com/rwightman/pytorch-image-models/blob/9a25fdf3ad0414b4d66da443fe60ae0aa14edc84/timm/models/efficientnet.py#L1487
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Config: ''
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In Collection: Noisy Student
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- Name: tf_efficientnet_b4_ns
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Metadata:
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FLOPs: 5749638672
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Epochs: 700
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Batch Size: 2048
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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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- AutoAugment
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- FixRes
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- Label Smoothing
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- Noisy Student
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- RMSProp
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- RandAugment
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- Weight Decay
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Training Resources: Cloud TPU v3 Pod
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Architecture:
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- 1x1 Convolution
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- Average Pooling
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- Batch Normalization
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- Convolution
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- Dense Connections
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- Dropout
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- Inverted Residual Block
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- Squeeze-and-Excitation Block
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- Swish
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File Size: 77995057
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Tasks:
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- Image Classification
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Training Time: ''
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ID: tf_efficientnet_b4_ns
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LR: 0.128
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Dropout: 0.5
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Crop Pct: '0.922'
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Momentum: 0.9
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Image Size: '380'
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Weight Decay: 1.0e-05
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Interpolation: bicubic
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RMSProp Decay: 0.9
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Label Smoothing: 0.1
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BatchNorm Momentum: 0.99
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Stochastic Depth Survival: 0.8
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Code: https://github.com/rwightman/pytorch-image-models/blob/9a25fdf3ad0414b4d66da443fe60ae0aa14edc84/timm/models/efficientnet.py#L1467
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Config: ''
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In Collection: Noisy Student
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- Name: tf_efficientnet_b7_ns
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Metadata:
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FLOPs: 48205304880
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Epochs: 350
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Batch Size: 2048
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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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- AutoAugment
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- FixRes
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- Label Smoothing
|
|
- Noisy Student
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- RMSProp
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|
- RandAugment
|
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- Weight Decay
|
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Training Resources: Cloud TPU v3 Pod
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Architecture:
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- 1x1 Convolution
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|
- Average Pooling
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|
- Batch Normalization
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|
- Convolution
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- Dense Connections
|
|
- Dropout
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- Inverted Residual Block
|
|
- Squeeze-and-Excitation Block
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- Swish
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|
File Size: 266853140
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Tasks:
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- Image Classification
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Training Time: ''
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ID: tf_efficientnet_b7_ns
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LR: 0.128
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Dropout: 0.5
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Crop Pct: '0.949'
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Momentum: 0.9
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Image Size: '600'
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Weight Decay: 1.0e-05
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Interpolation: bicubic
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RMSProp Decay: 0.9
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Label Smoothing: 0.1
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BatchNorm Momentum: 0.99
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Stochastic Depth Survival: 0.8
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|
Code: https://github.com/rwightman/pytorch-image-models/blob/9a25fdf3ad0414b4d66da443fe60ae0aa14edc84/timm/models/efficientnet.py#L1498
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Config: ''
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In Collection: Noisy Student
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Collections:
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- Name: Noisy Student
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Paper:
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title: Self-training with Noisy Student improves ImageNet classification
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url: https://paperswithcode.com//paper/self-training-with-noisy-student-improves
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type: model-index
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Type: model-index
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-->
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