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README.md CHANGED
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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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- - mozilla-foundation/common_voice_1_0
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  model-index:
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- - name: SpeechT5 TTS English Accented
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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 English Accented
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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 dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.6385
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  ## Model description
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@@ -40,21 +37,26 @@ More information needed
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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: 8
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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: 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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- | 0.7681 | 0.8 | 100 | 0.6385 |
 
 
 
 
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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: 0.4982
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  ## Model description
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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: 16
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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: 5000
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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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+ | 0.5383 | 16.0 | 1000 | 0.4644 |
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+ | 0.5126 | 32.0 | 2000 | 0.4858 |
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+ | 0.4753 | 48.0 | 3000 | 0.4889 |
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+ | 0.4666 | 64.0 | 4000 | 0.4931 |
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+ | 0.4836 | 80.0 | 5000 | 0.4982 |
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  ### Framework versions
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