Tejasva-Maurya/English-Technical-Speech-Dataset
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How to use Tejasva-Maurya/English_Technical_finetuned with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-to-audio", model="Tejasva-Maurya/English_Technical_finetuned") # Load model directly
from transformers import AutoProcessor, AutoModelForTextToSpectrogram
processor = AutoProcessor.from_pretrained("Tejasva-Maurya/English_Technical_finetuned")
model = AutoModelForTextToSpectrogram.from_pretrained("Tejasva-Maurya/English_Technical_finetuned")This model is a fine-tuned version of microsoft/speecht5_tts on an English Technical Speech 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 |
|---|---|---|---|
| 0.6122 | 0.3168 | 100 | 0.5289 |
| 0.5468 | 0.6337 | 200 | 0.4885 |
| 0.5207 | 0.9505 | 300 | 0.4745 |
| 0.5086 | 1.2673 | 400 | 0.4729 |
| 0.5012 | 1.5842 | 500 | 0.4638 |
| 0.4982 | 1.9010 | 600 | 0.4564 |
| 0.4888 | 2.2178 | 700 | 0.4528 |
| 0.4862 | 2.5347 | 800 | 0.4515 |
| 0.4866 | 2.8515 | 900 | 0.4454 |
| 0.4753 | 3.1683 | 1000 | 0.4451 |
Base model
microsoft/speecht5_tts