lowhipa-base-comb

This Whisper-for-IPA (WhIPA) model adapter is a PEFT LoRA fine-tuned version of openai/whisper-base on a subset of:

• CommonVoice11 dataset (1k samples each from Greek, Finnish, Hungarian, Japanese, Maltese, Polish, Tamil) with G2P-based IPA transcriptions
• Mandarin THCHS-30 database (https://arxiv.org/pdf/1512.01882) with IPA transcriptions by Taubert (2023, https://zenodo.org/records/7528596) (1k samples)
• Arabic Speech Corpus (https://en.arabicspeechcorpus.com) with custom IPA transcriptions transliterated from the provided Buckwalter transcriptions (1k samples) (https://doi.org/10.5281/zenodo.17111977)

Model description

For deployment and description, please refer to https://github.com/jshrdt/whipa.

from transformers import WhisperForConditionalGeneration, WhisperTokenizer, WhisperProcessor
from peft import PeftModel

tokenizer = WhisperTokenizer.from_pretrained("openai/whisper-base", task="transcribe")
tokenizer.add_special_tokens({"additional_special_tokens": ["<|ip|>"] + tokenizer.all_special_tokens})

base_model = WhisperForConditionalGeneration.from_pretrained("openai/whisper-base")
base_model.generation_config.lang_to_id["<|ip|>"] = tokenizer.convert_tokens_to_ids(["<|ip|>"])[0]
base_model.resize_token_embeddings(len(tokenizer))

whipa_model = PeftModel.from_pretrained(base_model, "jshrdt/lowhipa-base-comb")

whipa_model.generation_config.language = "<|ip|>"
whipa_model.generation_config.task = "transcribe"

whipa_processor = WhisperProcessor.from_pretrained("openai/whisper-base", task="transcribe")

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

Training results

Training Loss	Epoch	Validation Loss
1.5428	2.0323	1.2981462478637695
0.7498	4.0645	0.8457677960395813
0.5968	6.0968	0.759925901889801
0.5156	8.1290	0.7213243246078491
0.4603	10.1613	0.7064764499664307

Framework versions

• PEFT 0.15.1
• Transformers 4.48.3
• Pytorch 2.6.0+cu124
• Datasets 3.2.0
• Tokenizers 0.21.0