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--- |
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license: mit |
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tags: |
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- generated_from_trainer |
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datasets: |
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- facebook/voxpopuli |
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model-index: |
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- name: speecht5_finetuned_voxpopuli_pl_20epochs |
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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_pl_20epochs |
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This model is a fine-tuned version of [microsoft/speecht5_tts](https://huggingface.co/microsoft/speecht5_tts) on the facebook/voxpopuli dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4458 |
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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_ratio: 0.1 |
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- num_epochs: 20 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:----:|:---------------:| |
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| 0.6474 | 1.0 | 210 | 0.5754 | |
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| 0.558 | 2.0 | 421 | 0.4976 | |
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| 0.5292 | 3.0 | 632 | 0.4788 | |
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| 0.5174 | 4.0 | 843 | 0.4693 | |
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| 0.5063 | 5.0 | 1053 | 0.4639 | |
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| 0.5053 | 6.0 | 1264 | 0.4599 | |
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| 0.4968 | 7.0 | 1475 | 0.4570 | |
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| 0.4913 | 8.0 | 1686 | 0.4549 | |
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| 0.4895 | 9.0 | 1896 | 0.4532 | |
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| 0.4876 | 10.0 | 2107 | 0.4520 | |
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| 0.487 | 11.0 | 2318 | 0.4501 | |
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| 0.4805 | 12.0 | 2529 | 0.4484 | |
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| 0.4789 | 13.0 | 2739 | 0.4495 | |
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| 0.4853 | 14.0 | 2950 | 0.4469 | |
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| 0.4797 | 15.0 | 3161 | 0.4468 | |
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| 0.4758 | 16.0 | 3372 | 0.4458 | |
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| 0.4729 | 17.0 | 3582 | 0.4458 | |
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| 0.4744 | 18.0 | 3793 | 0.4461 | |
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| 0.4759 | 19.0 | 4004 | 0.4462 | |
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| 0.4759 | 19.93 | 4200 | 0.4461 | |
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### Framework versions |
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- Transformers 4.29.2 |
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- Pytorch 2.0.0 |
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- Datasets 2.13.1 |
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- Tokenizers 0.13.3 |
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