This model is a fine-tuned version of openai/whisper-medium on 10 hours of in-domain Kreol Morisien (Mauritian Creole) audio data, with accent conditioning.

Model Details

Parameter	Value
Base Model	`openai/whisper-medium`
Parameters	~769M
Language	Kreol Morisien (mfe)
Task	Transcription
Best WER	12.82%

Training Data

Domain: In-domain Kreol Morisien speech
Total Duration: ~15 hours
Split: 90% train / 10% validation
Format: 16kHz mono WAV
Preprocessing: Text normalization (lowercased, whitespace-collapsed, smart quotes replaced)

Training Configuration

Hyperparameter	Value
Epochs	10
Batch Size (per device)	8
Gradient Accumulation Steps	4
Effective Batch Size	32
Learning Rate	3e-5
LR Scheduler	Cosine
Warmup Steps	200
Weight Decay	0.1
Precision	bf16
Generation Beams (eval)	1 (greedy)
Best Checkpoint	Step 700

Training Results

Step	Training Loss	Validation Loss	WER
100	1.9289	0.3816	0.1964
200	0.4691	0.3208	0.1579
300	0.2571	0.3163	0.1499
400	0.1096	0.3442	0.1494
500	0.0398	0.3280	0.1360
600	0.0179	0.3312	0.1292
700	0.0046	0.3404	0.1282
750	0.0041	0.3405	0.1317

Usage

python

from transformers import WhisperProcessor, WhisperForConditionalGeneration
import soundfile as sf

processor = WhisperProcessor.from_pretrained("Shagufta/whisper-medium-km-indomain10-withac")
model = WhisperForConditionalGeneration.from_pretrained("Shagufta/whisper-medium-km-indomain10-withac")

speech, sr = sf.read("audio.wav", dtype="float32")

input_features = processor.feature_extractor(
    speech, sampling_rate=16000, return_tensors="pt"
).input_features

predicted_ids = model.generate(
    input_features,
    max_length=256,
    num_beams=5,
)

transcription = processor.tokenizer.batch_decode(predicted_ids, skip_special_tokens=True)[0]
print(transcription)

Model Config

python

model.config.forced_decoder_ids = None
model.config.suppress_tokens = []

Framework

Transformers (Seq2SeqTrainer)
Evaluate (WER metric)

Shagufta/whisper-medium-km-indomain15-withac

Whisper Medium — Kreol Morisien (In-Domain Fine-Tuned, With AC, 10h)

Model Details

Training Data

Training Configuration

Training Results

Usage

Model Config

Framework

Shagufta/
whisper-medium-km-indomain15-withac