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speecht5_english
eolang/speecht5_english
speecht5_english is a text-to-audio model from eolang. Use it for the text-to-audio task on the model card, and read the license before you ship it in a product. It is set up for transformers. The card lists the license as mit.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Text-to-Audio
- Library
- transformers
- License
- mit
- Model type
- speecht5
- Access
- Public
- Created
- Jan 8, 2026
- Updated
- Jan 8, 2026
- SHA
- dfa38135
Base models
Datasets
Model card
From the Hugging Face model README
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
speecht5_english
This model is a fine-tuned version of microsoft/speecht5_tts on the common_voice_22_0 dataset. It achieves the following results on the evaluation set:
- eval_loss: 0.5857
- eval_runtime: 1.8838
- eval_samples_per_second: 50.962
- eval_steps_per_second: 6.37
- epoch: 285.7407
- step: 4000
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.0001
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine_with_restarts
- lr_scheduler_warmup_steps: 500
- training_steps: 6000
- mixed_precision_training: Native AMP
Framework versions
- Transformers 4.57.3
- Pytorch 2.9.1+cu128
- Datasets 2.20.0
- Tokenizers 0.22.2
- Task
- Text-to-Audio
- Library
- transformers
- Type
- speecht5
- License
- mit
- Created
- Jan 8, 2026
- Updated
- Jan 8, 2026