google/fleurs
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How to use Shiry/whisper-large-v2-he-1 with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("automatic-speech-recognition", model="Shiry/whisper-large-v2-he-1") # Load model directly
from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq
processor = AutoProcessor.from_pretrained("Shiry/whisper-large-v2-he-1")
model = AutoModelForSpeechSeq2Seq.from_pretrained("Shiry/whisper-large-v2-he-1")This model is a fine-tuned version of openai/whisper-large-v2 on the google/fleurs he_il 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 |
|---|---|---|---|---|
| 0.425 | 24.01 | 50 | 0.4106 | 27.2504 |
| 0.1906 | 49.01 | 100 | 0.4420 | 29.0131 |
| 0.0982 | 74.01 | 150 | 0.4795 | 30.3063 |
| 0.0717 | 99.01 | 200 | 0.4945 | 30.8915 |