mozilla-foundation/common_voice_17_0
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How to use Harcuracy/whisper_bouesti_asr with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("automatic-speech-recognition", model="Harcuracy/whisper_bouesti_asr") # Load model directly
from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq
processor = AutoProcessor.from_pretrained("Harcuracy/whisper_bouesti_asr")
model = AutoModelForSpeechSeq2Seq.from_pretrained("Harcuracy/whisper_bouesti_asr")This model is a fine-tuned version of openai/whisper-small on the Common Voice 17.0 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 |
|---|---|---|---|---|
| 0.4516 | 0.8711 | 250 | 0.7315 | 55.8806 |
| 0.2582 | 1.7422 | 500 | 0.7210 | 51.2232 |
| 0.1496 | 2.6132 | 750 | 0.7389 | 50.6852 |
| 0.0913 | 3.4843 | 1000 | 0.7570 | 51.0383 |
Base model
openai/whisper-small