mozilla-foundation/common_voice_13_0
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How to use sanchit-gandhi/whisper-small-dv-4000-steps with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("automatic-speech-recognition", model="sanchit-gandhi/whisper-small-dv-4000-steps") # Load model directly
from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq
processor = AutoProcessor.from_pretrained("sanchit-gandhi/whisper-small-dv-4000-steps")
model = AutoModelForSpeechSeq2Seq.from_pretrained("sanchit-gandhi/whisper-small-dv-4000-steps", device_map="auto")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 |
|---|---|---|---|---|---|
| 0.0657 | 3.26 | 1000 | 0.1608 | 58.2144 | 11.9727 |
| 0.0117 | 6.51 | 2000 | 0.2264 | 58.2213 | 11.2060 |
| 0.0014 | 9.77 | 3000 | 0.2866 | 57.3438 | 11.1069 |
| 0.0002 | 13.03 | 4000 | 0.3057 | 56.5986 | 10.8339 |