mozilla-foundation/common_voice_13_0
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How to use juancopi81/whisper-small-dv with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("automatic-speech-recognition", model="juancopi81/whisper-small-dv") # Load model directly
from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq
processor = AutoProcessor.from_pretrained("juancopi81/whisper-small-dv")
model = AutoModelForSpeechSeq2Seq.from_pretrained("juancopi81/whisper-small-dv")This model is a fine-tuned version of openai/whisper-small on the Common Voice 13 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 |
|---|---|---|---|---|---|
| 0.1203 | 1.63 | 500 | 0.1687 | 62.7551 | 13.3724 |
| 0.0464 | 3.26 | 1000 | 0.1757 | 58.8899 | 12.0997 |
| 0.0327 | 4.89 | 1500 | 0.1931 | 59.0919 | 11.8510 |
| 0.0118 | 6.51 | 2000 | 0.2349 | 58.2492 | 11.4042 |
| 0.007 | 8.14 | 2500 | 0.2606 | 57.7408 | 11.5259 |
| 0.0056 | 9.77 | 3000 | 0.2759 | 57.4413 | 11.0564 |
| 0.0038 | 11.4 | 3500 | 0.2785 | 57.2185 | 10.9956 |
| 0.0039 | 13.03 | 4000 | 0.2937 | 56.7101 | 11.1190 |