This repository is an implementation of Model Agnostic Meta-Learning by Finn et al. in PyTorch.
Currently, the code supports first-order MAML (FOMAML) & the Omniglot dataset.
- Python 3.5.2
- Pytorch 1.3.1
- Torchmeta 1.2.1
This blog post by Oscar Knagg helped me immensely.
dataset: omniglot
num_ways: 5
num_shots: 1
meta:
training_iterations: 10000
batch_size: 16
lr: 1.0e-3
inner:
batch_size: 1
training_iterations: 1
lr: 0.4
logs:
val_interval: 100
writer_interval: 100
device: 'cpu' # or 'gpu'
python main.py
To check tensorboard, open up a command prompt and enter,
tensorboard --logdir=tensorboard-runs/
You can select the run ID from the list on the bottom left.