google/fleurs
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How to use arun100/whisper-base-fa-2 with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("automatic-speech-recognition", model="arun100/whisper-base-fa-2") # Load model directly
from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq
processor = AutoProcessor.from_pretrained("arun100/whisper-base-fa-2")
model = AutoModelForSpeechSeq2Seq.from_pretrained("arun100/whisper-base-fa-2")This model is a fine-tuned version of arun100/whisper-base-fa-1 on the google/fleurs fa_ir 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 |
|---|---|---|---|---|
| 0.1284 | 86.0 | 1000 | 0.5030 | 41.2338 |
| 0.0179 | 173.0 | 2000 | 0.5767 | 41.6119 |
| 0.0074 | 260.0 | 3000 | 0.6171 | 41.4478 |
| 0.0047 | 347.0 | 4000 | 0.6419 | 42.1791 |
| 0.0039 | 434.0 | 5000 | 0.6517 | 41.9751 |