affectscore-ace-step-r16-20260629

HiiragiLee/affectscore-ace-step-r16-20260629

affectscore-ace-step-r16-20260629 is a machine learning model from HiiragiLee. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for peft. The card lists the license as mit.

LoRA adapter for ACE-Step v1 3.5B fine-tuned for affect-conditioned game music generation. Lower-capacity rank variant from the AffectScore rank sweep (r ∈ {16, 32, 64}). r=32 was selected by held-out MER accuracy; th…

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At a glance

Library: peft
License: mit
Access: Public
Created: Jun 30, 2026
Updated: Aug 7, 2026
SHA: d52e867a

Base models

ACE-Step/ACE-Step-v1-3.5B

Model card

From the Hugging Face model README

AffectScore -- LoRA r=16

LoRA adapter for ACE-Step v1 3.5B fine-tuned for affect-conditioned game music generation. Lower-capacity rank variant from the AffectScore rank sweep (r ∈ {16, 32, 64}). r=32 was selected by held-out MER accuracy; this checkpoint is provided for reproducibility of the rank sweep.

Code and Colab notebooks: github.com/LeeTgk/affectscore (link active after publication)

Training

Parameter	Value
Base model	ACE-Step/ACE-Step-v1-3.5B
LoRA rank	16
LoRA targets	cross_attn.q_proj, cross_attn.v_proj
use_rslora	True
lora_dropout	0.05
Training clips	1,571 (CC0/CC-BY, CLAP-quality filtered)
Epochs	50
Learning rate	1e-4
Batch size	8
Hardware	NVIDIA A100 (Google Colab)

Training dataset: https://zenodo.org/records/21830658

Ablation variants

See affectscore-ace-step-r32-20260629 for full model details, evaluation results, and the complete variant table.

Citation

Citation will be added once the paper is published. If you use this model before then, please link to this repository.

Library: peft
License: mit
Created: Jun 30, 2026
Updated: Aug 7, 2026