PolyAI/minds14
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How to use Sandiago21/whisper-tiny-PolyAI-minds14 with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("automatic-speech-recognition", model="Sandiago21/whisper-tiny-PolyAI-minds14") # Load model directly
from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq
processor = AutoProcessor.from_pretrained("Sandiago21/whisper-tiny-PolyAI-minds14")
model = AutoModelForSpeechSeq2Seq.from_pretrained("Sandiago21/whisper-tiny-PolyAI-minds14")This model is a fine-tuned version of openai/whisper-tiny on the 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 |
|---|---|---|---|---|---|
| 4.995 | 1.0 | 29 | 2.9879 | 0.5425 | 0.4127 |
| 2.1634 | 2.0 | 58 | 0.8084 | 0.4382 | 0.3936 |
| 0.6659 | 3.0 | 87 | 0.6268 | 0.4144 | 0.3678 |
| 0.3865 | 4.0 | 116 | 0.5987 | 0.3880 | 0.3561 |
| 0.2428 | 5.0 | 145 | 0.6005 | 0.3990 | 0.3659 |
| 0.1734 | 6.0 | 174 | 0.6162 | 0.3906 | 0.3573 |
| 0.0965 | 7.0 | 203 | 0.6221 | 0.3893 | 0.3561 |
| 0.0682 | 8.0 | 232 | 0.6320 | 0.3803 | 0.3493 |
| 0.0473 | 9.0 | 261 | 0.6411 | 0.3797 | 0.3493 |
| 0.0476 | 10.0 | 290 | 0.6435 | 0.3797 | 0.3499 |
Base model
openai/whisper-tiny