Model Details
- Base model:
openai/whisper-large-v3-turbo
- Adapter type: PEFT LoRA
- LoRA rank: 16
- LoRA alpha: 32
- LoRA dropout: 0.05
- Target modules:
q_proj, v_proj
- Encoder: frozen during training
- Custom Whisper language token:
<|romani|>
- Decoder prompt:
<|romani|><|transcribe|><|notimestamps|>
Frozen Evaluation
All results below were rerun on 2026-08-10 with fixed manifests and guarded
decoding. Lower WER/CER is better.
Naming used below:
- Prompt Test =
test.csv, the original single-source prompt set
(R_prompts).
- Multi-Recording Dev =
validation_clean.csv, the cleaned multi-source
validation split.
- Whisper Turbo Baseline = base Whisper with a Slovak transcription prompt
and no Romani fine-tuning.
- Whisper Turbo Romani LoRA = this fine-tuned adapter.
- MMS-1B-All Romani/Latin Zero-Shot = public
facebook/mms-1b-all with
target_lang=rmc-script_latin, with no local MMS training.
Table with columns: Split, System, Role, WER, CER, ASCII WER, ASCII CER, Non-Latin| Split | System | Role | WER | CER | ASCII WER | ASCII CER | Non-Latin |
|---|
| Prompt Test | Whisper Turbo Baseline | unadapted baseline | 0.796 | 0.184 | 0.719 | 0.138 | 0 |
| Prompt Test | Whisper Turbo Romani LoRA | trained Whisper adapter | 0.653 |
Prompt Test contains one source group only, so it is useful for continuity with
the original model card but too easy to be the only headline result.
Multi-Recording Dev spans five recording groups and is a better stress test for
iteration.
The detailed frozen report is included in this repository at
eval/frozen-asr-evaluation-2026-08-10.md.
Known Limitations
This is an experimental low-resource ASR adapter. It still makes frequent
word-boundary, spelling, and diacritic mistakes. It is kept as a reproducible
Whisper adapter baseline while MMS adapter training is investigated separately.
The MMS rows above are comparison results only. This repository does not
contain an MMS adapter.
Intended Use
Use this adapter for experimentation with Latin-script Romani transcription.
Review transcripts before using them in user-facing or high-stakes settings.
Not Included
This repository does not include the base Whisper model, raw audio data,
training optimizer state, or training/evaluation logs.