Dev372/Medical_STT_Dataset_1.1
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How to use Dev372/Medical_base_en_1_1v with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("automatic-speech-recognition", model="Dev372/Medical_base_en_1_1v") # Load model directly
from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq
processor = AutoProcessor.from_pretrained("Dev372/Medical_base_en_1_1v")
model = AutoModelForSpeechSeq2Seq.from_pretrained("Dev372/Medical_base_en_1_1v")This model is a fine-tuned version of openai/whisper-tiny.en on the Medical 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 |
|---|---|---|---|---|
| 1.2361 | 0.2825 | 100 | 1.0425 | 10.4870 |
| 0.6631 | 0.5650 | 200 | 0.6451 | 9.4908 |
| 0.419 | 0.8475 | 300 | 0.3854 | 8.5535 |
| 0.1538 | 1.1299 | 400 | 0.1895 | 7.2635 |
| 0.1234 | 1.4124 | 500 | 0.1644 | 6.8454 |
| 0.1134 | 1.6949 | 600 | 0.1470 | 6.6201 |
| 0.1071 | 1.9774 | 700 | 0.1358 | 6.0289 |
| 0.0721 | 2.2599 | 800 | 0.1329 | 6.1302 |
| 0.0693 | 2.5424 | 900 | 0.1299 | 6.3065 |
| 0.0635 | 2.8249 | 1000 | 0.1275 | 6.5025 |
| 0.0441 | 3.1073 | 1100 | 0.1269 | 6.2869 |
Base model
openai/whisper-tiny.en