google/fleurs
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How to use anhphuong/whisper_largev2_jp with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("automatic-speech-recognition", model="anhphuong/whisper_largev2_jp") # Load model directly
from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq
processor = AutoProcessor.from_pretrained("anhphuong/whisper_largev2_jp")
model = AutoModelForSpeechSeq2Seq.from_pretrained("anhphuong/whisper_largev2_jp")This model is a fine-tuned version of openai/whisper-largev2-ja-v2 on the Google fleurs 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 |
|---|---|---|---|---|
| 0.004 | 6.25 | 1000 | 0.2030 | 61.0044 |
| 0.0022 | 12.5 | 2000 | 0.2081 | 60.6105 |
| 0.0002 | 18.75 | 3000 | 0.2401 | 58.7888 |
| 0.0001 | 25.0 | 4000 | 0.2531 | 58.6411 |
| 0.0001 | 31.25 | 5000 | 0.2598 | 58.2472 |
| 0.0001 | 37.5 | 6000 | 0.2626 | 58.2472 |