tbkazakova/even_speech_biblical
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How to use VovaK13/whisper-small-even with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("automatic-speech-recognition", model="VovaK13/whisper-small-even") # Load model directly
from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq
processor = AutoProcessor.from_pretrained("VovaK13/whisper-small-even")
model = AutoModelForSpeechSeq2Seq.from_pretrained("VovaK13/whisper-small-even")This model is a fine-tuned version of openai/whisper-small on the Even Speech Biblical 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 |
|---|---|---|---|---|
| 0.0509 | 5.9880 | 500 | 0.3699 | 33.7343 |
| 0.0022 | 11.9760 | 1000 | 0.4084 | 30.9273 |
| 0.0003 | 17.9641 | 1500 | 0.4336 | 30.1253 |
| 0.0002 | 23.9521 | 2000 | 0.4444 | 30.2757 |
| 0.0002 | 29.9401 | 2500 | 0.4483 | 30.2757 |
Base model
openai/whisper-small