Ffasr Pilot X Adapter Weights

--- base_model: efficient-speech/lite-whisper-large-v3-turbo-acc tags: - lora - peft - automatic-speech-recognition - whisper - ffasr --- # Pilot X u150 — LoRA weights only Raw LoRA adapter weights for a FFASR leaderboard submission, published separately from the full experiment writeup so the submission's custom evaluator script can fetch them without a token. - Base model: `efficient-speech/lite-whisper-large-v3-turbo-acc`, revision `ef2c0dd768cc9832a8a5a3397ab7218c838fea66`. Processor: `openai/whisper-large-v3`. - LoRA: rank 16, alpha 32, dropout 0.0 (inference), targeting `model.encoder.layers.*.self_attn.{q,v,out}_proj` and `model.decoder.layers.*.encoder_attn.{q,v,out}_proj`. - File: `adapter.safetensors` — a plain safetensors state dict from a small custom LoRA implementation (**not** the `peft` library): keys are the base model's module path plus `.lora_A` / `.lora_B`, loadable with `model.load_state_dict(tensors, strict=False)` after attaching equivalent `nn.Linear` LoRA wrappers at the module paths listed above. See the FFASR submission's custom evaluator script for a self-contained loader. This is a research checkpoint on an internal proxy eval set, not yet confirmed to beat the public FFASR baseline. No training code, decisions, or methodology are published here.

Source context: 0 downloads · 0 likes · Pipeline automatic-speech-recognition · Library peft · Repo banhchungtuongot/ffasr-pilot-x-adapter-weights