whipa-large-cv
Model details
This Whisper-for-IPA (WhIPA) model is a fine-tuned version of
openai/whisper-large-v2 on a subset of the CommonVoice11 dataset (1k samples each from Greek, Finnish, Hungarian, Japanese, Maltese, Polish, Tamil) with G2P-based IPA transcriptions.
It (6) achieves the following results on the evaluation set:
Loss: 0.5570
Lvnshtn: 5.9371
cer: 0.1709
cer_norm: 0.1604
ped: 5.5229
per: 0.1810
pfer: 5.7470
LhPD_(mipa): 2.0216
wefed: 17.9254
wefer: 0.5507
Epoch lvnshtn cer cer_norm ped per pfer LhPD_(mipa) wefed wefer time 2 8.382857142857137 0.24163589269510524 0.22863069089892205 7.757142857142851 0.2524059166580333 7.5604320437314785 2.6376535390328346 22.74642857142856 0.7052453948748261 3199.799334049225 4 6.691428571428563 0.19601619003578613 0.17116995643519559 6.197142857142849 0.20629669844107124 6.507800864530915 2.243887904361885 20.86178571428572 0.5902481277563488 6436.061186313629 6 5.9371428571428515 0.17092720391633578 0.1603608557874088 5.522857142857141 0.18096545655791033 5.746953179375352 2.021641668726793 17.925357142857134 0.5507118071695863 9660.67699599266 8 6.082857142857139 0.17536400979804245 0.1629698988097059 5.642857142857143 0.18555627617952597 5.993579904596805 2.100972125284737 18.620357142857138 0.57805324454652 12875.556059837341 10 6.134285714285711 0.1762981563905388 0.1632004044495094 5.668571428571428 0.1856530781701276 5.956850376357517 2.097938104613861 18.657499999999995 0.5731345760321149 16079.743387937546
Model description
For deployment and description, please refer to
https://github.com/jshrdt/whipa .
from transformers import WhisperForConditionalGeneration, WhisperTokenizer, WhisperProcessor
whipa_model = WhisperForConditionalGeneration.from_pretrained("jshrdt/whipa-large-cv")
whipa_model.generation_config.language = "<|ip|>"
whipa_model.generation_config.task = "transcribe"
whipa_tokenizer = WhisperTokenizer.from_pretrained("jshrdt/whipa-large-cv", task="transcribe")
whipa_processor = WhisperProcessor.from_pretrained("jshrdt/whipa-large-cv", task="transcribe")
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