PolyAI/minds14
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How to use ykirpichev/whisper-tiny-en-us with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("automatic-speech-recognition", model="ykirpichev/whisper-tiny-en-us") # Load model directly
from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq
processor = AutoProcessor.from_pretrained("ykirpichev/whisper-tiny-en-us")
model = AutoModelForSpeechSeq2Seq.from_pretrained("ykirpichev/whisper-tiny-en-us")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 |
|---|---|---|---|---|---|
| 2.1622 | 1.79 | 50 | 0.9646 | 0.4510 | 0.3908 |
| 0.3628 | 3.57 | 100 | 0.5673 | 0.3812 | 0.3501 |
| 0.131 | 5.36 | 150 | 0.5827 | 0.3714 | 0.3436 |
| 0.0488 | 7.14 | 200 | 0.6058 | 0.3689 | 0.3383 |
| 0.0144 | 8.93 | 250 | 0.6444 | 0.3671 | 0.3430 |
| 0.0044 | 10.71 | 300 | 0.6652 | 0.3418 | 0.3282 |
| 0.0021 | 12.5 | 350 | 0.6827 | 0.3405 | 0.3306 |
| 0.0013 | 14.29 | 400 | 0.6956 | 0.3448 | 0.3341 |
| 0.0011 | 16.07 | 450 | 0.7061 | 0.3640 | 0.3542 |
Base model
openai/whisper-tiny