google/fleurs
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How to use Viraj008/whisper-small-mr_v5 with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("automatic-speech-recognition", model="Viraj008/whisper-small-mr_v5") # Load model directly
from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq
processor = AutoProcessor.from_pretrained("Viraj008/whisper-small-mr_v5")
model = AutoModelForSpeechSeq2Seq.from_pretrained("Viraj008/whisper-small-mr_v5")This model is a fine-tuned version of Viraj008/whisper-small-mr_v4 on the Common Voice 17.0, 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 |
|---|---|---|---|---|
| 0.0573 | 0.5355 | 1000 | 0.2405 | 36.3370 |
| 0.0314 | 1.0710 | 2000 | 0.2484 | 35.4172 |
| 0.0298 | 1.6064 | 3000 | 0.2410 | 35.1640 |
| 0.0182 | 2.1419 | 4000 | 0.2496 | 34.1242 |
Base model
openai/whisper-small