naharte/japanese_english
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How to use Quiglee2/whisper-tiny-japanese-ft with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("automatic-speech-recognition", model="Quiglee2/whisper-tiny-japanese-ft") # pip install -U transformers accelerate
# Load model directly
from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq
processor = AutoProcessor.from_pretrained("Quiglee2/whisper-tiny-japanese-ft")
model = AutoModelForSpeechSeq2Seq.from_pretrained("Quiglee2/whisper-tiny-japanese-ft", device_map="auto")This model is a fine-tuned version of openai/whisper-tiny on the Japanese English 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 |
|---|---|---|---|---|
| 0.1368 | 1.2438 | 1000 | 0.4810 | 22.0865 |
| 0.0896 | 2.4876 | 2000 | 0.4626 | 21.3972 |
Base model
openai/whisper-tiny