PolyAI/minds14
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How to use ditwoo/whisper-tiny-PolyAI-minds14 with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("automatic-speech-recognition", model="ditwoo/whisper-tiny-PolyAI-minds14") # Load model directly
from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq
processor = AutoProcessor.from_pretrained("ditwoo/whisper-tiny-PolyAI-minds14")
model = AutoModelForSpeechSeq2Seq.from_pretrained("ditwoo/whisper-tiny-PolyAI-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 |
|---|---|---|---|---|---|
| 2.1657 | 1.0 | 28 | 1.5460 | 0.4913 | 0.4168 |
| 0.4751 | 2.0 | 56 | 0.5582 | 0.3872 | 0.3757 |
| 0.346 | 3.0 | 84 | 0.5050 | 0.3622 | 0.3518 |
| 0.2062 | 4.0 | 112 | 0.4995 | 0.3797 | 0.3661 |
| 0.1223 | 5.0 | 140 | 0.5165 | 0.3547 | 0.3435 |
| 0.069 | 6.0 | 168 | 0.5367 | 0.3516 | 0.3351 |
| 0.0311 | 7.0 | 196 | 0.5545 | 0.3741 | 0.3643 |
| 0.013 | 8.0 | 224 | 0.5766 | 0.3822 | 0.3661 |
| 0.0075 | 9.0 | 252 | 0.5770 | 0.3441 | 0.3339 |
| 0.0037 | 10.0 | 280 | 0.5977 | 0.3485 | 0.3423 |