Pseudo-Labelling
Pseudo Labelling on MNIST dataset in Tensorflow 2.x (by consequencesunintended)
ganbert-pytorch
Enhancing the BERT training with Semi-supervised Generative Adversarial Networks in Pytorch/HuggingFace (by crux82)
| Pseudo-Labelling | ganbert-pytorch | |
|---|---|---|
| 1 | 1 | |
| 9 | 88 | |
| - | - | |
| 0.0 | 0.0 | |
| almost 2 years ago | over 2 years ago | |
| Jupyter Notebook | Jupyter Notebook | |
| - | Apache License 2.0 |
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Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Pseudo-Labelling
Posts with mentions or reviews of Pseudo-Labelling.
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ganbert-pytorch
Posts with mentions or reviews of ganbert-pytorch.
We have used some of these posts to build our list of alternatives
and similar projects.
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GAN-BERT to resolve class imbalance; error in the / my code. Any ideas how to resolve this?
I'm sorry to ask such an oddly specific question. I am following Danilo Croce's git page for implementing GAN-BERT with PyTorch & Transformers: Link. The training gets all the way to the end of the first epoch, but before it completes, sends out an error in the last batch (e.g. it occurs on batch 1,275 of 1,275):
What are some alternatives?
When comparing Pseudo-Labelling and ganbert-pytorch you can also consider the following projects:
PAWS-TF - Minimal implementation of PAWS (https://arxiv.org/abs/2104.13963) in TensorFlow.
stylegan-encoder - StyleGAN Encoder - converts real images to latent space
ETCI-2021-Competition-on-Flood-Detection - Experiments on Flood Segmentation on Sentinel-1 SAR Imagery with Cyclical Pseudo Labeling and Noisy Student Training
ganspace - Discovering Interpretable GAN Controls [NeurIPS 2020]