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Tips for Successfully Training Transformers on Small Datasets
It turns out that you can easily train transformers on small datasets when you use tricks (and have the patience to train a very long time).
transformers small-datasets training ptb
A Recipe for Training Neural Networks
The most common neural net mistakes and listing a few common gotchas related to training neural nets.
systems-design checklist training debugging
Customizing What Happens in Fit()
How to leverage the convenient features of fit() with a custom training loop.
tensorflow keras training tutorial
Data Project Checklist
There’s a lot more to creating useful data projects than just training an accurate model!
product-management databases training checklist
Train ALBERT for NLP with TensorFlow on Amazon SageMaker
To train BERT in 1 hour, we efficiently scaled out to 2,048 NVIDIA V100 GPUs by improving the underlying infrastructure, network, and ML framework.
bert transformers albert natural-language-processing
PyTorch CNN Trainer
A simple package to fine-tune CNNs from torchvision and Pytorch Image models by Ross Wightman.
torchvision convolutional-neural-networks pytorch training
Training GANs - From Theory to Practice
Optimizing min-max loss functions that arise in training GANs.
generative-adversarial-networks training loss loss-functions
TOMA: Torch Memory-adaptive Algorithms
Helps you write algorithms in PyTorch that adapt to the available (CUDA) memory.
training cuda lstm gpu
An Overview of Distributed Training of Deep Learning Models
Overview of the different techniques that are used by contemporary distributed DL systems and discuss their influence and implications on the training ...
distributed-training training overview arxiv:2007.03970
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