This is an ablation of our Distilled Voice Assistant (DiVA) model which can handle speech and text as inputs. This ablation is trained using only distillation loss as described in the ablations here: https://huggingface.co/papers/2410.02678
@misc{held2024diva,
author="Held, Will and Zhang, Yanzhe and Ryan, Michael and Shi, Weiyan and Li, Ella and Yang, Diyi",
title="Distilling an End-to-End Voice Assistant from Speech Recognition Data",
year="2024",
publisher="HuggingFace",
}
This model was trained for 7k gradient steps with a batch size of 512 Recordings and a linearly decaying learning rate from 5e-5 to zero, with a linear warmup of 70 steps.
Environmental Impact
Hardware Type: V4-32 TPU
Hours used: 8 Hours
Cloud Provider: Google Cloud.
Compute Region: US Central C
Hardware
This model was trained on at V4 TPU on Google Cloud.
