google/fleurs
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How to use ihanif/whisper_small_ps_augmented with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("automatic-speech-recognition", model="ihanif/whisper_small_ps_augmented") # Load model directly
from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq
processor = AutoProcessor.from_pretrained("ihanif/whisper_small_ps_augmented")
model = AutoModelForSpeechSeq2Seq.from_pretrained("ihanif/whisper_small_ps_augmented")This model is a fine-tuned version of openai/whisper-small on the google/fleurs 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 | Cer |
|---|---|---|---|---|---|
| 0.9683 | 1.19 | 100 | 0.8812 | 139.3765 | 131.6166 |
| 0.6848 | 2.38 | 200 | 0.7543 | 145.9973 | 151.3369 |
| 0.5548 | 3.57 | 300 | 0.6979 | 53.6244 | 22.6847 |