Dev372/Medical_STT_Dataset_1.1
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How to use Dev372/Medical_small_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_small_en_1_1v") # Load model directly
from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq
processor = AutoProcessor.from_pretrained("Dev372/Medical_small_en_1_1v")
model = AutoModelForSpeechSeq2Seq.from_pretrained("Dev372/Medical_small_en_1_1v")This model is a fine-tuned version of openai/whisper-small.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 |
|---|---|---|---|---|
| 0.7956 | 0.2825 | 100 | 0.7275 | 8.0048 |
| 0.5277 | 0.5650 | 200 | 0.5046 | 6.2706 |
| 0.2247 | 0.8475 | 300 | 0.1916 | 6.1988 |
| 0.0883 | 1.1299 | 400 | 0.1251 | 5.5880 |
| 0.0735 | 1.4124 | 500 | 0.1173 | 5.0883 |
| 0.0752 | 1.6949 | 600 | 0.1080 | 4.9120 |
| 0.0689 | 1.9774 | 700 | 0.0975 | 4.5233 |
| 0.0401 | 2.2599 | 800 | 0.0992 | 4.4613 |
| 0.0364 | 2.5424 | 900 | 0.0966 | 4.7291 |
| 0.0345 | 2.8249 | 1000 | 0.0952 | 4.8891 |
Base model
openai/whisper-small.en