mozilla-foundation/common_voice_13_0
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How to use fmagot01/whisper-small-dv-second with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("automatic-speech-recognition", model="fmagot01/whisper-small-dv-second") # Load model directly
from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq
processor = AutoProcessor.from_pretrained("fmagot01/whisper-small-dv-second")
model = AutoModelForSpeechSeq2Seq.from_pretrained("fmagot01/whisper-small-dv-second")This model is a fine-tuned version of openai/whisper-small on the Common Voice 13 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 Ortho | Wer | Cer |
|---|---|---|---|---|---|---|
| 0.1995 | 0.81 | 250 | 0.2387 | 0.7319 | 0.1888 | 0.1330 |
| 0.1215 | 1.63 | 500 | 0.1689 | 0.6258 | 0.1350 | 0.0963 |
Base model
openai/whisper-small