Caution
This is an intermediate checkpoint.
Model Details
We have developed and released the family llama3s. This family is natively understanding audio and text input.
We continual pretrain on the expanded vocabulary homebrewltd/llama3.1-s-whispervq-init with 900M tokens from homebrewltd/raw-speech-whispervq-v1 dataset.
Model developers Homebrew Research.
Input Text and sound.
Output Text.
Model Architecture Llama-3.
Language(s): English.
Intended Use
Intended Use Cases This family is primarily intended for research applications. This version aims to further improve the LLM on sound understanding capabilities.
Out-of-scope The use of llama3-s in any manner that violates applicable laws or regulations is strictly prohibited.
Hardware
GPU Configuration: Cluster of 10x NVIDIA A6000-48GB.
GPU Usage:
- Continual Training: 30 hours.
Training Arguments
We utilize torchtune library for the latest FSDP2 training code implementation.
| Parameter | Continual Training |
|---|---|
| Epoch | 1 |
| Global batch size | 480 |
| Learning Rate | 2e-4 |
| Learning Scheduler | Cosine with warmup |
| Optimizer | AdamW fused |
| Warmup Steps | 50 |
| Weight Decay | 0.01 |
| Max Sequence Length | 512 |
| Max Training Steps | 2000 |
Citation Information
BibTeX:
@article{Llama3-S: Sound Instruction Language Model 2024,
title={Llama3-S},
author={Homebrew Research},
year=2024,
month=August},
url={https://huggingface.co/homebrewltd/llama3.1-s-2024-08-15}
Acknowledgement
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