This is a fine-tune of the 7B model of VibeVoice. Requires 21.9GB of VRAM for inference (through OpenVoiceLab)
Fine-tuning was done using the code available here:
https://github.com/voicepowered-ai/VibeVoice-finetuning
Fine-tuning parameters used were:
batch_size = 1
drop_rate = 0.2
grad_accum = 1
lr = 2.5e-5
lora_r = 128
lora_alpha = 512
epochs = 20
train_diff = True
bf16 = True
grad_clip = True
max_grad = 0.8
grad_checkpoint = False
diff_weight = 1.4
ce_weight = 0.04
warmup = 0.03
scheduler = "cosine"
Special thanks to mrfakename, for creating OpenVoiceLab, a fantastic resource for both inference, and fine-tuning, with quite a nice GUI.