PolyAI/minds14
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How to use cvnberk/whisper-tiny with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("automatic-speech-recognition", model="cvnberk/whisper-tiny") # Load model directly
from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq
processor = AutoProcessor.from_pretrained("cvnberk/whisper-tiny")
model = AutoModelForSpeechSeq2Seq.from_pretrained("cvnberk/whisper-tiny")This model is a fine-tuned version of openai/whisper-small on the PolyAI/minds14 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 |
|---|---|---|---|---|---|
| 0.8427 | 1.32 | 50 | 0.5401 | 35.9655 | 0.3566 |
| 0.1982 | 2.63 | 100 | 0.5179 | 35.5336 | 0.3501 |
| 0.0531 | 3.95 | 150 | 0.5197 | 31.6471 | 0.3117 |
Base model
openai/whisper-tiny