mozilla-foundation/common_voice_13_0
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How to use Siim303/whisper-small-et with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("automatic-speech-recognition", model="Siim303/whisper-small-et") # Load model directly
from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq
processor = AutoProcessor.from_pretrained("Siim303/whisper-small-et")
model = AutoModelForSpeechSeq2Seq.from_pretrained("Siim303/whisper-small-et")This model is a fine-tuned version of openai/whisper-small on the Common Voice 13 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 Ortho | Wer |
|---|---|---|---|---|---|
| 0.4004 | 1.3850 | 500 | 0.5864 | 47.6554 | 44.6803 |
Base model
openai/whisper-small