yashtiwari/PaulMooney-Medical-ASR-Data
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How to use DeFamy/whisper-medium-medical with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("automatic-speech-recognition", model="DeFamy/whisper-medium-medical", device_map="auto") # Load model directly
from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq
processor = AutoProcessor.from_pretrained("DeFamy/whisper-medium-medical")
model = AutoModelForSpeechSeq2Seq.from_pretrained("DeFamy/whisper-medium-medical", device_map="auto")This model is a fine-tuned version of openai/whisper-medium on the Medical ASR 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 |
|---|---|---|---|---|
| 0.3456 | 0.5405 | 100 | 0.2379 | 17.6684 |
| 0.1514 | 1.0811 | 200 | 0.1298 | 15.7615 |
| 0.0846 | 1.6216 | 300 | 0.0976 | 19.7924 |
| 0.0479 | 2.1622 | 400 | 0.0881 | 19.3338 |
| 0.0272 | 2.7027 | 500 | 0.0829 | 19.5269 |
Base model
openai/whisper-medium