Arbi-Houssem/Tunisian_dataset_STT-TTS15s_filtred1.0_Mixed
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How to use Arbi-Houssem/speecht5_ar_tn_1.4 with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-to-audio", model="Arbi-Houssem/speecht5_ar_tn_1.4") # Load model directly
from transformers import AutoProcessor, AutoModelForTextToSpectrogram
processor = AutoProcessor.from_pretrained("Arbi-Houssem/speecht5_ar_tn_1.4")
model = AutoModelForTextToSpectrogram.from_pretrained("Arbi-Houssem/speecht5_ar_tn_1.4")This model is a fine-tuned version of MBZUAI/speecht5_tts_clartts_ar on the Tunisian_dataset_STT-TTS15s_filtred1.0_Mixed 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 |
|---|---|---|---|
| 0.6355 | 6.6667 | 500 | 0.5657 |
| 0.5548 | 13.3333 | 1000 | 0.5314 |
| 0.539 | 20.0 | 1500 | 0.5286 |
| 0.5475 | 26.6667 | 2000 | 0.5220 |
| 0.5031 | 33.3333 | 2500 | 0.5193 |
| 0.5077 | 40.0 | 3000 | 0.5174 |
| 0.4724 | 46.6667 | 3500 | 0.4577 |
| 0.54 | 53.3333 | 4000 | 0.4610 |
Base model
MBZUAI/speecht5_tts_clartts_ar