PolyAI/minds14
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How to use markkeung/whisper-tiny-minds14-en-us with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("automatic-speech-recognition", model="markkeung/whisper-tiny-minds14-en-us") # pip install -U transformers accelerate
# Load model directly
from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq
processor = AutoProcessor.from_pretrained("markkeung/whisper-tiny-minds14-en-us")
model = AutoModelForSpeechSeq2Seq.from_pretrained("markkeung/whisper-tiny-minds14-en-us", device_map="auto")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 | Wer Ortho |
|---|---|---|---|---|---|
| 0.3972 | 1.7857 | 100 | 0.4791 | 0.3595 | 0.3732 |
| 0.1725 | 3.5714 | 200 | 0.4744 | 0.3241 | 0.3362 |
| 0.0939 | 5.0 | 280 | 0.4832 | 0.3335 | 0.3473 |
Base model
openai/whisper-tiny