ahishamm/QURANICWhisperDataset
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How to use ahishamm/finetuned-whisper-quranic-large-v3-2 with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("automatic-speech-recognition", model="ahishamm/finetuned-whisper-quranic-large-v3-2") # Load model directly
from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq
processor = AutoProcessor.from_pretrained("ahishamm/finetuned-whisper-quranic-large-v3-2")
model = AutoModelForSpeechSeq2Seq.from_pretrained("ahishamm/finetuned-whisper-quranic-large-v3-2", device_map="auto")This model is a fine-tuned version of openai/whisper-large-v3 on the QURANICWhisperDataset dataset. It achieves the following results on the evaluation set:
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The following hyperparameters were used during training:
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.0862 | 2.0 | 1000 | 0.1308 | 162.4365 |
| 0.0489 | 4.0 | 2000 | 0.1305 | 168.4432 |
| 0.0111 | 6.0 | 3000 | 0.1499 | 193.2011 |
| 0.0013 | 8.0 | 4000 | 0.1663 | 112.0268 |
Base model
openai/whisper-large-v3