japanese-asr/ja_asr.common_voice_8_0
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How to use kdl02/whisper-small-ja with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("automatic-speech-recognition", model="kdl02/whisper-small-ja") # Load model directly
from transformers import AutoProcessor, AutoModelForMultimodalLM
processor = AutoProcessor.from_pretrained("kdl02/whisper-small-ja")
model = AutoModelForMultimodalLM.from_pretrained("kdl02/whisper-small-ja")This model is a fine-tuned version of openai/whisper-small on the Common Voice 8.0 Japanese 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 |
|---|---|---|---|---|
| 0.0349 | 3.7453 | 1000 | 0.2838 | 71.8062 |
| 0.0031 | 7.4906 | 2000 | 0.3100 | 69.6035 |
| 0.0007 | 11.2360 | 3000 | 0.3358 | 70.9251 |
| 0.0003 | 14.9813 | 4000 | 0.3474 | 73.5683 |
| 0.0002 | 18.7266 | 5000 | 0.3555 | 73.1278 |
| 0.0002 | 22.4719 | 6000 | 0.3663 | 73.1278 |
| 0.0001 | 26.2172 | 7000 | 0.3732 | 72.2467 |
| 0.0001 | 29.9625 | 8000 | 0.3763 | 72.2467 |
Base model
openai/whisper-small