mozilla-foundation/common_voice_17_0
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How to use PenguinbladeZ/whisper-small-hk with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("automatic-speech-recognition", model="PenguinbladeZ/whisper-small-hk") # Load model directly
from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq
processor = AutoProcessor.from_pretrained("PenguinbladeZ/whisper-small-hk")
model = AutoModelForSpeechSeq2Seq.from_pretrained("PenguinbladeZ/whisper-small-hk")This model is a fine-tuned version of openai/whisper-small on the Common Voice 16.0, the Common Voice 16.1 and the Common Voice 17.0 datasets. 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 |
|---|---|---|---|---|
| 0.0845 | 0.7087 | 1000 | 0.2773 | 61.5120 |
| 0.0285 | 1.4174 | 2000 | 0.2697 | 56.7010 |
| 0.0102 | 2.1262 | 3000 | 0.2650 | 55.6319 |
Base model
openai/whisper-small