PolyAI/minds14
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How to use Maimonator/whisper-tiny-en with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("automatic-speech-recognition", model="Maimonator/whisper-tiny-en") # Load model directly
from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq
processor = AutoProcessor.from_pretrained("Maimonator/whisper-tiny-en")
model = AutoModelForSpeechSeq2Seq.from_pretrained("Maimonator/whisper-tiny-en")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 |
|---|---|---|---|---|---|
| 0.6838 | 1.79 | 50 | 0.6522 | 0.4028 | 0.3613 |
| 0.2778 | 3.57 | 100 | 0.5727 | 0.3880 | 0.3589 |
| 0.1313 | 5.36 | 150 | 0.5870 | 0.3794 | 0.3501 |
| 0.0539 | 7.14 | 200 | 0.6080 | 0.3726 | 0.3471 |
| 0.022 | 8.93 | 250 | 0.6380 | 0.3745 | 0.3477 |
| 0.0095 | 10.71 | 300 | 0.6629 | 0.3843 | 0.3595 |
| 0.0049 | 12.5 | 350 | 0.6715 | 0.3819 | 0.3583 |
| 0.0036 | 14.29 | 400 | 0.6811 | 0.3825 | 0.3595 |
| 0.0032 | 16.07 | 450 | 0.6858 | 0.3757 | 0.3554 |
| 0.0029 | 17.86 | 500 | 0.6875 | 0.3745 | 0.3542 |