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--- |
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language: |
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- en |
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license: mit |
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base_model: microsoft/speecht5_tts |
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tags: |
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- TTS, |
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- generated_from_trainer |
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datasets: |
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- lj_speech |
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model-index: |
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- name: SpeechT5 TTS LJ_Speech |
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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 LJ_Speech |
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This model is a fine-tuned version of [microsoft/speecht5_tts](https://huggingface.co/microsoft/speecht5_tts) on the lj_speech dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3659 |
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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: 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: 10000 |
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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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| 0.4059 | 2.7137 | 1000 | 0.3729 | |
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| 0.3927 | 5.4274 | 2000 | 0.3707 | |
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| 0.3982 | 8.1411 | 3000 | 0.3696 | |
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| 0.4006 | 10.8548 | 4000 | 0.3682 | |
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| 0.3869 | 13.5685 | 5000 | 0.3669 | |
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| 0.395 | 16.2822 | 6000 | 0.3669 | |
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| 0.4012 | 18.9959 | 7000 | 0.3666 | |
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| 0.3858 | 21.7096 | 8000 | 0.3662 | |
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| 0.3864 | 24.4233 | 9000 | 0.3658 | |
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| 0.3982 | 27.1370 | 10000 | 0.3659 | |
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### Framework versions |
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- Transformers 4.41.0.dev0 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.19.0 |
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- Tokenizers 0.19.1 |
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