En1gma02/indian_accent_english
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How to use rishithabcdefghijklmnop/custom with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-to-audio", model="rishithabcdefghijklmnop/custom") # pip install -U transformers accelerate
# Load model directly
from transformers import AutoProcessor, AutoModelForTextToSpectrogram
processor = AutoProcessor.from_pretrained("rishithabcdefghijklmnop/custom")
model = AutoModelForTextToSpectrogram.from_pretrained("rishithabcdefghijklmnop/custom", device_map="auto")This model is a fine-tuned version of microsoft/speecht5_tts on the indian_accent_english 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 |
|---|---|---|---|
| 0.5341 | 0.6570 | 1000 | 0.4899 |
| 0.5078 | 1.3141 | 2000 | 0.4635 |
| 0.4703 | 1.9711 | 3000 | 0.4352 |
| 0.4579 | 2.6281 | 4000 | 0.4205 |
| 0.455 | 3.2852 | 5000 | 0.4173 |
| 0.4643 | 3.9422 | 6000 | 0.4100 |
| 0.4493 | 4.5992 | 7000 | 0.4029 |
| 0.4208 | 5.2562 | 8000 | 0.3991 |
| 0.4468 | 5.9133 | 9000 | 0.4017 |
| 0.4117 | 6.5703 | 10000 | 0.3974 |
Base model
microsoft/speecht5_tts