Arbi-Houssem/Tunisian_dataset_STT-TTS30s_filtred1.0
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How to use Arbi-Houssem/TunLangModel_test30s with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("automatic-speech-recognition", model="Arbi-Houssem/TunLangModel_test30s") # Load model directly
from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq
processor = AutoProcessor.from_pretrained("Arbi-Houssem/TunLangModel_test30s")
model = AutoModelForSpeechSeq2Seq.from_pretrained("Arbi-Houssem/TunLangModel_test30s", device_map="auto")This model is a fine-tuned version of openai/whisper-small on the Tunisian_dataset_STT-TTS30s_filtred1.0 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 |
|---|---|---|---|---|
| 0.1045 | 8.4746 | 500 | 3.3315 | 102.7898 |
| 0.0043 | 16.9492 | 1000 | 3.7250 | 103.1746 |
Base model
openai/whisper-small