facebook/multilingual_librispeech
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How to use ClementXie/speecht5_finetuned_multilingual_librispeech_italian9h with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-to-speech", model="ClementXie/speecht5_finetuned_multilingual_librispeech_italian9h") # Load model directly
from transformers import AutoProcessor, AutoModelForTextToSpectrogram
processor = AutoProcessor.from_pretrained("ClementXie/speecht5_finetuned_multilingual_librispeech_italian9h")
model = AutoModelForTextToSpectrogram.from_pretrained("ClementXie/speecht5_finetuned_multilingual_librispeech_italian9h", device_map="auto")This model is a fine-tuned version of microsoft/speecht5_tts on the multilingual_librispeech 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 |
|---|---|---|---|
| 0.5378 | 7.75 | 250 | 0.4721 |
| 0.4872 | 15.5 | 500 | 0.4424 |
| 0.4766 | 23.26 | 750 | 0.4363 |
| 0.4784 | 31.01 | 1000 | 0.4342 |