Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
Safetensors
Japanese
whisper
whisper-event
Generated from Trainer
Eval Results (legacy)
Instructions to use vumichien/whisper-small-ja with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use vumichien/whisper-small-ja with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="vumichien/whisper-small-ja")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("vumichien/whisper-small-ja") model = AutoModelForSpeechSeq2Seq.from_pretrained("vumichien/whisper-small-ja", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Much difference in evaluation results on google/fleurs dataset
#3
by AICoding91 - opened
Thank you for amazing repo.
I tried to evalute your model on google/fleurs dataset. Because you did not provide evaluation source code, so I based on whisper-small https://huggingface.co/openai/whisper-small#evaluation
I changed dataset google/fleurs, but I got very big WER. It is much different from your reported WER on google/fleurs dataset.
Could you please provide evaluation source code for this model? Thank you so much.
And I also saw, when running inference, you model gives spaces between Japanese characters. It did not happen with the original model whisper-small. Is there any special config in your finetuning process?