This model is an INT8 quantized Faster-Whisper version of openai/whisper-base, converted from MinaNasser/Whisper-Small-MN using CTranslate2.

It is optimized for fast Arabic speech recognition with low memory usage.

Performance

Loss: 0.5446
WER: 49.9256
CER: 28.5219

Quantization Details

Setting	Value
Runtime	ctranslate2
Compute type	float16
Optimization	faster-whisper
Conversion tool	ctranslate2

Training Data

Dataset: Arabic_STT_DS_AI_Transcriped
Language: Arabic

Intended Use

Fast Arabic ASR
Real-time transcription
CPU & low-VRAM GPU inference
Edge & production deployment

Limitations

INT8 quantization may slightly reduce accuracy
Trained on a single Arabic dataset
Dialect generalization is not guaranteed

Inference Example (Faster-Whisper)

python

from faster_whisper import WhisperModel

model = WhisperModel(
    "MinaNasser/Whisper-Base-MN-EG-int8",
    compute_type="int8"
)

segments, info = model.transcribe("audio.wav", language="ar")

for segment in segments:
    print(segment.text)
    

MinaNasser/Whisper-Small-MN-f16

Whisper-Base-MN-EG-int8 (Faster-Whisper)