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--- |
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base_model: Daniel981215/speecht5-tts-finetuned-es-voxpopuli-commonvoice16 |
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tags: |
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- generated_from_trainer |
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datasets: |
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- mozilla-foundation/common_voice_16_1 |
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model-index: |
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- name: speecht5-tts-finetuned-es-voxpopuli-commonvoice16 |
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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-es-voxpopuli-commonvoice16 |
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This model is a fine-tuned version of [Daniel981215/speecht5-tts-finetuned-es-voxpopuli-commonvoice16](https://huggingface.co/Daniel981215/speecht5-tts-finetuned-es-voxpopuli-commonvoice16) on the mozilla-foundation/common_voice_16_1 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4681 |
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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: 8 |
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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: 64 |
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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: 500 |
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- training_steps: 10000 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:------:|:-----:|:---------------:| |
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| 0.5187 | 0.1953 | 1000 | 0.4877 | |
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| 0.5038 | 0.3906 | 2000 | 0.4823 | |
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| 0.5063 | 0.5859 | 3000 | 0.4788 | |
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| 0.5018 | 0.7812 | 4000 | 0.4744 | |
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| 0.4958 | 0.9764 | 5000 | 0.4728 | |
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| 0.4981 | 1.1717 | 6000 | 0.4713 | |
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| 0.4944 | 1.3670 | 7000 | 0.4703 | |
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| 0.4949 | 1.5623 | 8000 | 0.4683 | |
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| 0.4902 | 1.7576 | 9000 | 0.4687 | |
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| 0.4924 | 1.9529 | 10000 | 0.4681 | |
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### Framework versions |
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- Transformers 4.41.0.dev0 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.19.0 |
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- Tokenizers 0.19.1 |
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