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--- |
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library_name: transformers |
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license: mit |
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base_model: microsoft/speecht5_tts |
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tags: |
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- generated_from_trainer |
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datasets: |
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- voxpopuli/fi |
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model-index: |
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- name: speecht5_finetuned_voxpopuli_fi_lim_speakrs |
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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_fi_lim_speakrs |
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This model is a fine-tuned version of [microsoft/speecht5_tts](https://huggingface.co/microsoft/speecht5_tts) on the voxpopuli/fi dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4429 |
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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: 10 |
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- eval_batch_size: 2 |
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- seed: 42 |
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- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_steps: 250 |
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- training_steps: 8000 |
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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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| 0.5587 | 1.25 | 500 | 0.4937 | |
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| 0.5176 | 2.5 | 1000 | 0.4703 | |
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| 0.4983 | 3.75 | 1500 | 0.4594 | |
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| 0.5016 | 5.0 | 2000 | 0.4584 | |
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| 0.4797 | 6.25 | 2500 | 0.4539 | |
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| 0.4845 | 7.5 | 3000 | 0.4512 | |
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| 0.4882 | 8.75 | 3500 | 0.4489 | |
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| 0.4721 | 10.0 | 4000 | 0.4469 | |
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| 0.4829 | 11.25 | 4500 | 0.4456 | |
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| 0.4974 | 12.5 | 5000 | 0.4457 | |
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| 0.4776 | 13.75 | 5500 | 0.4442 | |
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| 0.4866 | 15.0 | 6000 | 0.4441 | |
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| 0.4752 | 16.25 | 6500 | 0.4430 | |
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| 0.4765 | 17.5 | 7000 | 0.4430 | |
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| 0.4668 | 18.75 | 7500 | 0.4431 | |
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| 0.4823 | 20.0 | 8000 | 0.4429 | |
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### Framework versions |
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- Transformers 4.46.2 |
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- Pytorch 2.5.1+cu121 |
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- Datasets 3.1.0 |
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- Tokenizers 0.20.3 |
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