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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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- generated_from_trainer
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datasets:
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- common_voice_13_0
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model-index:
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- name: test8k
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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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# test8k
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This model is a fine-tuned version of [microsoft/speecht5_tts](https://huggingface.co/microsoft/speecht5_tts) on the common_voice_13_0 dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.5429
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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: 0.0001
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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: 100
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- training_steps: 3000
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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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| 0.7829 | 0.76 | 100 | 0.6936 |
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| 0.6812 | 1.53 | 200 | 0.6392 |
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| 0.6544 | 2.29 | 300 | 0.6275 |
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| 0.6337 | 3.05 | 400 | 0.6147 |
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| 0.6214 | 3.81 | 500 | 0.5963 |
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| 0.602 | 4.58 | 600 | 0.5894 |
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| 0.6078 | 5.34 | 700 | 0.5902 |
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| 0.5892 | 6.1 | 800 | 0.5854 |
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| 0.5842 | 6.86 | 900 | 0.5751 |
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| 0.5836 | 7.63 | 1000 | 0.5691 |
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| 0.5712 | 8.39 | 1100 | 0.5722 |
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| 0.5734 | 9.15 | 1200 | 0.5654 |
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| 0.5669 | 9.91 | 1300 | 0.5539 |
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| 0.5575 | 10.68 | 1400 | 0.5629 |
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| 0.5638 | 11.44 | 1500 | 0.5594 |
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| 0.5522 | 12.2 | 1600 | 0.5550 |
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| 0.5585 | 12.96 | 1700 | 0.5515 |
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| 0.5488 | 13.73 | 1800 | 0.5492 |
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| 0.5536 | 14.49 | 1900 | 0.5579 |
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| 0.5353 | 15.25 | 2000 | 0.5533 |
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| 0.5379 | 16.02 | 2100 | 0.5434 |
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| 0.5369 | 16.78 | 2200 | 0.5495 |
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| 0.5375 | 17.54 | 2300 | 0.5441 |
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| 0.5285 | 18.3 | 2400 | 0.5473 |
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| 0.5262 | 19.07 | 2500 | 0.5369 |
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| 0.5242 | 19.83 | 2600 | 0.5464 |
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| 0.5219 | 20.59 | 2700 | 0.5414 |
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| 0.5132 | 21.35 | 2800 | 0.5426 |
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| 0.517 | 22.12 | 2900 | 0.5442 |
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| 0.5097 | 22.88 | 3000 | 0.5429 |
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### Framework versions
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- Transformers 4.39.3
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- Pytorch 2.3.0+cu118
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- Datasets 3.0.0
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- Tokenizers 0.15.2
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