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--- |
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library_name: transformers |
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language: |
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- nl |
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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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- maguette |
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model-index: |
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- name: SpeechT5 TTS MT V2 |
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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 MT V2 |
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This model is a fine-tuned version of [microsoft/speecht5_tts](https://huggingface.co/microsoft/speecht5_tts) on the maguette dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4931 |
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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: 16 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 32 |
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- optimizer: Use OptimizerNames.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: 10 |
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- training_steps: 200 |
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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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| No log | 6.6667 | 10 | 1.1093 | |
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| No log | 13.3333 | 20 | 0.9983 | |
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| 1.1116 | 20.0 | 30 | 0.9168 | |
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| 1.1116 | 26.6667 | 40 | 0.8119 | |
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| 0.8005 | 33.3333 | 50 | 0.7925 | |
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| 0.8005 | 40.0 | 60 | 0.7629 | |
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| 0.8005 | 46.6667 | 70 | 0.7380 | |
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| 0.738 | 53.3333 | 80 | 0.6968 | |
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| 0.738 | 60.0 | 90 | 0.6487 | |
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| 0.677 | 66.6667 | 100 | 0.6119 | |
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| 0.677 | 73.3333 | 110 | 0.5832 | |
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| 0.677 | 80.0 | 120 | 0.5555 | |
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| 0.5968 | 86.6667 | 130 | 0.5425 | |
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| 0.5968 | 93.3333 | 140 | 0.5329 | |
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| 0.5626 | 100.0 | 150 | 0.5180 | |
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| 0.5626 | 106.6667 | 160 | 0.5074 | |
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| 0.5626 | 113.3333 | 170 | 0.5100 | |
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| 0.5461 | 120.0 | 180 | 0.5035 | |
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| 0.5461 | 126.6667 | 190 | 0.4918 | |
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| 0.5208 | 133.3333 | 200 | 0.4931 | |
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### Framework versions |
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- Transformers 4.46.3 |
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- Pytorch 2.6.0+cu124 |
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- Datasets 3.1.0 |
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- Tokenizers 0.20.3 |
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