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--- |
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language: |
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- ita |
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base_model: microsoft/speecht5-tts |
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tags: |
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- text-to-speech |
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datasets: |
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- facebook/multilingual_librispeech |
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model-index: |
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- name: speecht5-finetuned-ita |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# speecht5_tts-finetuned-multilingual_librispeech |
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This model is a fine-tuned version of [microsoft/speecht5_tts](https://huggingface.co/microsoft/speecht5_tts) on the multilingual_librispeech dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4342 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 1e-05 |
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- train_batch_size: 4 |
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- eval_batch_size: 2 |
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- seed: 42 |
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- gradient_accumulation_steps: 8 |
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- total_train_batch_size: 32 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_steps: 200 |
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- training_steps: 1000 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:----:|:---------------:| |
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| 0.5378 | 7.75 | 250 | 0.4721 | |
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| 0.4872 | 15.5 | 500 | 0.4424 | |
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| 0.4766 | 23.26 | 750 | 0.4363 | |
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| 0.4784 | 31.01 | 1000 | 0.4342 | |
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### Framework versions |
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- Transformers 4.32.0.dev0 |
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- Pytorch 1.13.1 |
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- Datasets 2.14.3 |
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- Tokenizers 0.13.2 |
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