Dev372/Medical_STT_Dataset_1.0
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How to use trsree/whisper-newts with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("automatic-speech-recognition", model="trsree/whisper-newts") # Load model directly
from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq
processor = AutoProcessor.from_pretrained("trsree/whisper-newts")
model = AutoModelForSpeechSeq2Seq.from_pretrained("trsree/whisper-newts", device_map="auto")This model is a fine-tuned version of trsree/whisper-newts on the Medical STT dataset 1.0 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 |
|---|---|---|---|---|
| 0.0024 | 9.0090 | 1000 | 0.0574 | 1.3237 |
| 0.0001 | 18.0180 | 2000 | 0.0559 | 1.3934 |
| 0.0002 | 27.0270 | 3000 | 0.0584 | 1.4166 |
| 0.0 | 36.0360 | 4000 | 0.0594 | 1.4166 |
Unable to build the model tree, the base model loops to the model itself. Learn more.