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JBZhang2342
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speecht5_tts

Text-to-Audio
Transformers
TensorBoard
Safetensors
English
speecht5
en_accent,mozilla,t5,common_voice_1_0
Generated from Trainer
Inference Endpoints
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  1. README.md +19 -17
  2. model.safetensors +1 -1
README.md CHANGED
@@ -1,26 +1,23 @@
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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: 0.5103
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  ## Model description
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@@ -39,7 +36,7 @@ More information needed
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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: 16
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  - seed: 42
@@ -48,18 +45,23 @@ The following hyperparameters were used during training:
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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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- | 0.5407 | 16.0 | 1000 | 0.4686 |
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- | 0.4995 | 32.0 | 2000 | 0.4828 |
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- | 0.4729 | 48.0 | 3000 | 0.4939 |
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- | 0.4733 | 64.0 | 4000 | 0.5020 |
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- | 0.4901 | 80.0 | 5000 | 0.5103 |
 
 
 
 
 
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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: 0.5189
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  ## Model description
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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+ - learning_rate: 2e-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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  - 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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+ | 0.5395 | 16.0 | 1000 | 0.4726 |
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+ | 0.4727 | 32.0 | 2000 | 0.4819 |
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+ | 0.4513 | 48.0 | 3000 | 0.4871 |
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+ | 0.4526 | 64.0 | 4000 | 0.5006 |
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+ | 0.4474 | 80.0 | 5000 | 0.5022 |
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+ | 0.4147 | 96.0 | 6000 | 0.5039 |
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+ | 0.423 | 112.0 | 7000 | 0.5154 |
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+ | 0.4271 | 128.0 | 8000 | 0.5217 |
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+ | 0.4232 | 144.0 | 9000 | 0.5198 |
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+ | 0.4044 | 160.0 | 10000 | 0.5189 |
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  ### Framework versions
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