atlasia/darija_bible_aligned
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How to use basbao/whisper-tiny-finetune-Moroccan-darija with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("automatic-speech-recognition", model="basbao/whisper-tiny-finetune-Moroccan-darija") # Load model directly
from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq
processor = AutoProcessor.from_pretrained("basbao/whisper-tiny-finetune-Moroccan-darija")
model = AutoModelForSpeechSeq2Seq.from_pretrained("basbao/whisper-tiny-finetune-Moroccan-darija")This model is a fine-tuned version of openai/whisper-tiny on the darija_bible_aligned 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 |
|---|---|---|---|---|
| 0.1766 | 0.7037 | 1000 | 0.1846 | 20.2502 |
| 0.0822 | 1.4075 | 2000 | 0.1040 | 11.5558 |
| 0.0402 | 2.1112 | 3000 | 0.0713 | 7.8442 |
| 0.0331 | 2.8149 | 4000 | 0.0556 | 5.8004 |
| 0.0201 | 3.5186 | 5000 | 0.0494 | 5.2240 |
Base model
openai/whisper-tiny