mozilla-foundation/common_voice_17_0
Updated • 5.39k • 17
How to use zuazo/whisper-tiny-eu-cv17_0 with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("automatic-speech-recognition", model="zuazo/whisper-tiny-eu-cv17_0") # Load model directly
from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq
processor = AutoProcessor.from_pretrained("zuazo/whisper-tiny-eu-cv17_0")
model = AutoModelForSpeechSeq2Seq.from_pretrained("zuazo/whisper-tiny-eu-cv17_0")This model is a fine-tuned version of openai/whisper-tiny on the mozilla-foundation/common_voice_17_0 eu 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 |
|---|---|---|---|---|
| 0.0348 | 9.3458 | 1000 | 0.3382 | 22.7152 |
| 0.0021 | 18.6916 | 2000 | 0.4092 | 21.7844 |
| 0.0009 | 28.0374 | 3000 | 0.4509 | 21.9026 |
| 0.0023 | 37.3832 | 4000 | 0.4062 | 20.7181 |
| 0.0003 | 46.7290 | 5000 | 0.4350 | 20.1244 |
| 0.0002 | 56.0748 | 6000 | 0.4546 | 20.1702 |
| 0.0001 | 65.4206 | 7000 | 0.4745 | 20.2179 |
| 0.0001 | 74.7664 | 8000 | 0.4941 | 20.1995 |
| 0.0 | 84.1121 | 9000 | 0.5142 | 20.3342 |
| 0.0 | 93.4579 | 10000 | 0.5353 | 20.4386 |
| 0.0 | 102.8037 | 11000 | 0.5567 | 20.5495 |
| 0.0 | 112.1495 | 12000 | 0.5788 | 20.6100 |
| 0.0 | 121.4953 | 13000 | 0.6023 | 20.6988 |
| 0.0 | 130.8411 | 14000 | 0.6253 | 20.7767 |
| 0.0 | 140.1869 | 15000 | 0.6486 | 20.8683 |
Base model
openai/whisper-tiny