mozilla-foundation/common_voice_13_0
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How to use rishabbahal/whisper-base-hi with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("automatic-speech-recognition", model="rishabbahal/whisper-base-hi") # Load model directly
from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq
processor = AutoProcessor.from_pretrained("rishabbahal/whisper-base-hi")
model = AutoModelForSpeechSeq2Seq.from_pretrained("rishabbahal/whisper-base-hi")This model is a fine-tuned version of openai/whisper-base on the Common Voice 13.0 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 |
|---|---|---|---|---|
| 0.2093 | 2.3641 | 1000 | 0.4135 | 48.6273 |
| 0.0898 | 4.7281 | 2000 | 0.4273 | 45.7038 |
| 0.0279 | 7.0922 | 3000 | 0.4794 | 45.6334 |
| 0.0166 | 9.4563 | 4000 | 0.5202 | 46.0226 |
Base model
openai/whisper-base