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---
datasets:
- homebrewltd/instruction-speech-whispervq-v2
language:
- en
license: apache-2.0
tags:
- sound language model
---
## Model Details
We have developed and released the family [llama3s](https://huggingface.co/collections/homebrew-research/llama3-s-669df2139f0576abc6eb7405). This family is natively understanding audio and text input.
We continual pretrain on the expanded vocabulary [homebrewltd/llama3.1-s-whispervq-init](https://huggingface.co/homebrewltd/llama3.1-s-whispervq-init) with 900M tokens from [homebrewltd/raw-speech-whispervq-v1](https://huggingface.co/datasets/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.
## Training process
**Training Metrics Image**: Below is a snapshot of the training loss curve visualized.
**MMLU**:
| Model | MMLU Score |
| --- | --- |
| llama3.5-instruct-8b | 69.40 |
| ichigo-llama3.1-s-v0.3: phase 3 | 63.79 |
| ichigo-llama3.1-s-v0.3: phase 2 | 63.08 |
| ichigo-llama3.1-s-base-v0.3 | **42.11** |
| llama3.5-instruct-v0.2 | 50.27 |
### Hardware
**GPU Configuration**: Cluster of 10x NVIDIA A6000-48GB.
**GPU Usage**:
- **Continual Training**: 30 hours.
### Training Arguments
We utilize [torchtune](https://github.com/pytorch/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 |
## 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
- **[WhisperSpeech](https://github.com/collabora/WhisperSpeech)**
- **[Meta-Llama-3.1-8B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3.1-8B-Instruct)** |