Arbi-Houssem/Tunisian_dataset_STT-TTS
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How to use Arbi-Houssem/TunLangModel1.5 with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("automatic-speech-recognition", model="Arbi-Houssem/TunLangModel1.5") # Load model directly
from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq
processor = AutoProcessor.from_pretrained("Arbi-Houssem/TunLangModel1.5")
model = AutoModelForSpeechSeq2Seq.from_pretrained("Arbi-Houssem/TunLangModel1.5")This model is a fine-tuned version of openai/whisper-small on the Tunisian_dataset_STT-TTS 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 |
|---|---|---|---|---|
| 0.2639 | 5.7471 | 500 | 2.8790 | 103.3635 |
| 0.0292 | 11.4943 | 1000 | 3.4175 | 131.9534 |
| 0.0045 | 17.2414 | 1500 | 3.7135 | 106.2743 |
| 0.0021 | 22.9885 | 2000 | 3.7732 | 119.7930 |
| 0.0012 | 28.7356 | 2500 | 3.8911 | 124.9677 |
| 0.0004 | 34.4828 | 3000 | 3.9580 | 130.2717 |
| 0.0003 | 40.2299 | 3500 | 3.9781 | 108.7969 |
| 0.0003 | 45.9770 | 4000 | 3.9898 | 111.1902 |
Base model
openai/whisper-small