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Model save
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README.md
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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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- en_accent,mozilla,t5,common_voice_1_0
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- generated_from_trainer
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datasets:
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model-index:
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- name:
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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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#
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This model is a fine-tuned version of [microsoft/speecht5_tts](https://huggingface.co/microsoft/speecht5_tts) on the
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It achieves the following results on the evaluation set:
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- Loss: 0.
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## Model description
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- total_train_batch_size: 16
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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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- training_steps: 4000
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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.
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| 0.5048 | 16.0 | 2000 | 0.4554 |
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| 0.4809 | 24.0 | 3000 | 0.4450 |
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| 0.4903 | 32.0 | 4000 | 0.4468 |
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### Framework versions
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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_1_0
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model-index:
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- name: speecht5_tts
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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
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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_1_0 dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.6337
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## Model description
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- total_train_batch_size: 16
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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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- training_steps: 100
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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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| 0.7822 | 0.8 | 100 | 0.6337 |
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### Framework versions
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