mozilla-foundation/common_voice_17_0
Updated • 5.99k • 18
How to use rigun/whisper-medium-id-002 with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("automatic-speech-recognition", model="rigun/whisper-medium-id-002") # Load model directly
from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq
processor = AutoProcessor.from_pretrained("rigun/whisper-medium-id-002")
model = AutoModelForSpeechSeq2Seq.from_pretrained("rigun/whisper-medium-id-002")This model is a fine-tuned version of openai/whisper-medium 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 |
|---|---|---|---|---|
| 0.1352 | 1.9231 | 1000 | 0.1943 | 13.3695 |
| 0.0167 | 3.8462 | 2000 | 0.2161 | 12.6131 |
| 0.0024 | 5.7692 | 3000 | 0.2483 | 12.5064 |
| 0.0008 | 7.6923 | 4000 | 0.2638 | 12.8776 |
Base model
openai/whisper-medium