DigitalUmuganda/Afrivoice_legacy
Updated • 5 • 3
How to use KasuleTrevor/whisper-lingala-small-test-5 with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("automatic-speech-recognition", model="KasuleTrevor/whisper-lingala-small-test-5") # Load model directly
from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq
processor = AutoProcessor.from_pretrained("KasuleTrevor/whisper-lingala-small-test-5")
model = AutoModelForSpeechSeq2Seq.from_pretrained("KasuleTrevor/whisper-lingala-small-test-5")This model is a fine-tuned version of openai/whisper-small on the AfriVoice 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 |
|---|---|---|---|---|
| 0.0308 | 16.1290 | 500 | 0.9322 | 41.8411 |
| 0.0011 | 32.2581 | 1000 | 1.0521 | 40.6692 |
Base model
openai/whisper-small