google/fleurs
Viewer • Updated • 768k • 57.2k • 403
How to use nesrine19/whisper_model_team1-ar with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("automatic-speech-recognition", model="nesrine19/whisper_model_team1-ar") # Load model directly
from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq
processor = AutoProcessor.from_pretrained("nesrine19/whisper_model_team1-ar")
model = AutoModelForSpeechSeq2Seq.from_pretrained("nesrine19/whisper_model_team1-ar")This model is a fine-tuned version of openai/whisper-medium on the fleurs data dataset. It achieves the following results on the evaluation set:
More information needed
More information needed
More information needed
The following hyperparameters were used during training:
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.0001 | 76.92 | 1000 | 0.9206 | 45.2860 |
Base model
openai/whisper-medium