PolyAI/minds14
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How to use davidggphy/whisper-tiny-finetuned-minds14-enUS with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("automatic-speech-recognition", model="davidggphy/whisper-tiny-finetuned-minds14-enUS") # Load model directly
from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq
processor = AutoProcessor.from_pretrained("davidggphy/whisper-tiny-finetuned-minds14-enUS")
model = AutoModelForSpeechSeq2Seq.from_pretrained("davidggphy/whisper-tiny-finetuned-minds14-enUS")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 | Cer | Cer Ortho |
|---|---|---|---|---|---|---|---|
| 0.0136 | 7.14 | 100 | 0.6142 | 0.3362 | 0.3388 | 0.2587 | 0.2614 |
| 0.0009 | 14.29 | 200 | 0.6704 | 0.3288 | 0.3300 | 0.2515 | 0.2534 |
| 0.0011 | 21.43 | 300 | 0.6858 | 0.3054 | 0.3093 | 0.2363 | 0.2374 |
| 0.0005 | 28.57 | 400 | 0.7081 | 0.3455 | 0.3477 | 0.2699 | 0.2711 |
| 0.0004 | 35.71 | 500 | 0.7191 | 0.3467 | 0.3501 | 0.2727 | 0.2736 |
| 0.0001 | 42.86 | 600 | 0.7337 | 0.3405 | 0.3447 | 0.2652 | 0.2662 |
| 0.0001 | 50.0 | 700 | 0.7418 | 0.3393 | 0.3430 | 0.2636 | 0.2645 |
| 0.0001 | 57.14 | 800 | 0.7466 | 0.3387 | 0.3424 | 0.2634 | 0.2644 |
| 0.0001 | 64.29 | 900 | 0.7496 | 0.3350 | 0.3388 | 0.2604 | 0.2614 |
| 0.0001 | 71.43 | 1000 | 0.7508 | 0.3356 | 0.3394 | 0.2613 | 0.2623 |
Base model
openai/whisper-tiny