google/fleurs
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How to use ihanif/whisper-medium-pashto with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("automatic-speech-recognition", model="ihanif/whisper-medium-pashto") # Load model directly
from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq
processor = AutoProcessor.from_pretrained("ihanif/whisper-medium-pashto")
model = AutoModelForSpeechSeq2Seq.from_pretrained("ihanif/whisper-medium-pashto")This model is a fine-tuned version of openai/whisper-medium on the google/fleurs ps_af 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 |
|---|---|---|---|---|
| 0.0334 | 14.29 | 100 | 1.0348 | 50.0908 |
| 0.0021 | 28.57 | 200 | 1.1971 | 49.4855 |
| 0.0007 | 42.86 | 300 | 1.2651 | 49.7352 |
| 0.0006 | 57.14 | 400 | 1.3084 | 49.9697 |
| 0.0005 | 71.43 | 500 | 1.3479 | 50.0605 |
| 0.0004 | 85.71 | 600 | 1.3835 | 50.3027 |
| 0.0004 | 100.0 | 700 | 1.4139 | 50.4540 |
| 0.0004 | 114.29 | 800 | 1.4382 | 50.4616 |
| 0.0004 | 128.57 | 900 | 1.4545 | 50.5297 |
| 0.0003 | 142.86 | 1000 | 1.4603 | 50.5675 |
| 0.0003 | 157.14 | 1100 | 1.4750 | 50.5599 |
| 0.0003 | 171.43 | 1200 | 1.4807 | 50.5448 |
Base model
openai/whisper-medium