google/fleurs
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How to use julie200/whisper-small-xh_za with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("automatic-speech-recognition", model="julie200/whisper-small-xh_za") # pip install -U transformers accelerate
# Load model directly
from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq
processor = AutoProcessor.from_pretrained("julie200/whisper-small-xh_za")
model = AutoModelForSpeechSeq2Seq.from_pretrained("julie200/whisper-small-xh_za", device_map="auto")This model is a fine-tuned version of openai/whisper-small on the google/fleurs xh_za 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 |
|---|---|---|---|---|
| 0.583 | 7.01 | 100 | 1.0822 | 67.3176 |
| 0.1146 | 14.02 | 200 | 1.1217 | 65.9512 |