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--- |
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license: mit |
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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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- voxpopuli |
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model-index: |
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- name: speecht5_finetuned_voxpopuli_sl |
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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_finetuned_voxpopuli_sl |
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This model is a fine-tuned version of [microsoft/speecht5_tts](https://huggingface.co/microsoft/speecht5_tts) on the voxpopuli dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5157 |
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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: 2 |
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- eval_batch_size: 2 |
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- seed: 42 |
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- gradient_accumulation_steps: 16 |
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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: 500 |
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- training_steps: 4000 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:------:|:----:|:---------------:| |
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| 0.5152 | 91.95 | 500 | 0.5177 | |
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| 0.4734 | 183.91 | 1000 | 0.5199 | |
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| 0.4555 | 275.86 | 1500 | 0.5129 | |
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| 0.4464 | 367.82 | 2000 | 0.5133 | |
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| 0.437 | 459.77 | 2500 | 0.5097 | |
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| 0.4342 | 551.72 | 3000 | 0.5152 | |
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| 0.426 | 643.68 | 3500 | 0.5153 | |
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| 0.426 | 735.63 | 4000 | 0.5157 | |
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### Framework versions |
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- Transformers 4.33.0.dev0 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.14.4 |
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- Tokenizers 0.13.3 |
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