EYEDOL/naija-voices-yoruba-split_0-6
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How to use EYEDOL/whisper-tiny-yoruba3 with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("automatic-speech-recognition", model="EYEDOL/whisper-tiny-yoruba3") # Load model directly
from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq
processor = AutoProcessor.from_pretrained("EYEDOL/whisper-tiny-yoruba3")
model = AutoModelForSpeechSeq2Seq.from_pretrained("EYEDOL/whisper-tiny-yoruba3")This model is a fine-tuned version of EYEDOL/whisper-tiny-yoruba2 on the EYEDOL/naija-voices-yoruba-split_0-6 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 |
|---|---|---|---|---|---|
| 1.4417 | 1.0 | 583 | 0.7132 | 0.7172 | 0.6352 |
| 1.3179 | 2.0 | 1166 | 0.7039 | 0.6964 | 0.6110 |
| 1.2151 | 3.0 | 1749 | 0.7038 | 0.7101 | 0.6275 |
| 1.1268 | 4.0 | 2332 | 0.7058 | 0.7037 | 0.6166 |
| 1.0504 | 5.0 | 2915 | 0.7111 | 0.7096 | 0.6293 |
Unable to build the model tree, the base model loops to the model itself. Learn more.