Request for Detailed Hyperparameters in LOTUS Experiments #6
Description
Dear Dr. Weikang Wan and Team,
I recently came across your fascinating work on the LOTUS algorithm, as detailed in your paper "LOTUS: Continual Imitation Learning for Robot Manipulation Through Unsupervised Skill Discovery."
Your approach to lifelong robot learning through unsupervised skill discovery is truly impressive and offers significant insights into continual imitation learning for robot manipulation. I am particularly interested in replicating and building upon your experiments as part of my research.
However, I noticed that the paper does not provide specific details on some of the experimental hyperparameters, such as the learning rate, number of epochs, and batch size used during training. These details are crucial for ensuring that my replication is as accurate as possible.
Could you kindly provide the following details:
The learning rate(s) used for training the models.
The number of epochs each model was trained for.
The batch size used during training.
Any other relevant hyperparameters or settings that were critical to the performance of the LOTUS algorithm.
I greatly appreciate your time and assistance. Your work is a significant contribution to the field, and having these details would be immensely helpful for my research.
Thank you very much for your support and I look forward to your response.
Best regards