PolyAI/minds14
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How to use magnustragardh/whisper-tiny-en-minds14 with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("automatic-speech-recognition", model="magnustragardh/whisper-tiny-en-minds14") # Load model directly
from transformers import AutoProcessor, AutoModelForMultimodalLM
processor = AutoProcessor.from_pretrained("magnustragardh/whisper-tiny-en-minds14")
model = AutoModelForMultimodalLM.from_pretrained("magnustragardh/whisper-tiny-en-minds14")This model is a fine-tuned version of openai/whisper-tiny 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 |
|---|---|---|---|---|---|
| 1.4576 | 1.79 | 50 | 0.9286 | 0.3128 | 0.3152 |
| 0.3694 | 3.57 | 100 | 0.5188 | 0.2776 | 0.2774 |
| 0.0466 | 5.36 | 150 | 0.4494 | 0.2640 | 0.2692 |
| 0.008 | 7.14 | 200 | 0.4855 | 0.2782 | 0.2816 |
| 0.0026 | 8.93 | 250 | 0.4892 | 0.2801 | 0.2845 |
| 0.0016 | 10.71 | 300 | 0.5116 | 0.2745 | 0.2774 |
| 0.0004 | 12.5 | 350 | 0.5383 | 0.2770 | 0.2798 |
| 0.0002 | 14.29 | 400 | 0.5471 | 0.2758 | 0.2774 |
| 0.0002 | 16.07 | 450 | 0.5590 | 0.2714 | 0.2733 |
| 0.0001 | 17.86 | 500 | 0.5680 | 0.2721 | 0.2745 |