mozilla-foundation/common_voice_17_0
Updated • 6.15k • 18
How to use ArzhurKoadek/whisper-small-br with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("automatic-speech-recognition", model="ArzhurKoadek/whisper-small-br") # Load model directly
from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq
processor = AutoProcessor.from_pretrained("ArzhurKoadek/whisper-small-br")
model = AutoModelForSpeechSeq2Seq.from_pretrained("ArzhurKoadek/whisper-small-br")This model is a fine-tuned version of openai/whisper-small on the Common Voice 17.0 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 |
|---|---|---|---|---|
| 0.168 | 3.2468 | 1000 | 0.7951 | 53.9458 |
| 0.0124 | 6.4935 | 2000 | 0.8755 | 51.6273 |
| 0.0016 | 9.7403 | 3000 | 0.9224 | 52.6509 |
| 0.0009 | 12.9870 | 4000 | 0.9421 | 52.2397 |
Base model
openai/whisper-small