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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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- . |
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- generated_from_trainer |
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datasets: |
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- speecht5_imda_nsc_p1 |
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model-index: |
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- name: Speech T5 TTS English |
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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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# Speech T5 TTS English |
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This model is a fine-tuned version of [microsoft/speecht5_tts](https://huggingface.co/microsoft/speecht5_tts) on the IMDA National Speech Corpus dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3968 |
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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: 32 |
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- eval_batch_size: 64 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 64 |
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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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- num_epochs: 10.0 |
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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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| 0.4693 | 0.91 | 1000 | 0.4240 | |
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| 0.4524 | 1.82 | 2000 | 0.4132 | |
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| 0.4405 | 2.72 | 3000 | 0.4079 | |
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| 0.4416 | 3.63 | 4000 | 0.4056 | |
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| 0.4298 | 4.54 | 5000 | 0.4009 | |
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| 0.4363 | 5.45 | 6000 | 0.4002 | |
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| 0.4301 | 6.35 | 7000 | 0.3989 | |
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| 0.4376 | 7.26 | 8000 | 0.3978 | |
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| 0.4308 | 8.17 | 9000 | 0.3984 | |
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| 0.4363 | 9.08 | 10000 | 0.3971 | |
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| 0.4341 | 9.99 | 11000 | 0.3968 | |
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### Framework versions |
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- Transformers 4.35.2 |
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- Pytorch 2.1.1+cu121 |
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- Datasets 2.15.0 |
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- Tokenizers 0.15.0 |
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