speecht5_finetuned_VCTK_dataset_kavinda
This model is a fine-tuned version of microsoft/speecht5_tts on the vctk dataset. It achieves the following results on the evaluation set:
- Loss: 0.4222
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: 4
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 32
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- training_steps: 500
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 4.5548 | 0.0403 | 100 | 0.5333 |
| 4.2726 | 0.0807 | 200 | 0.4616 |
| 3.8866 | 0.1210 | 300 | 0.4378 |
| 3.8037 | 0.1613 | 400 | 0.4314 |
| 3.7014 | 0.2017 | 500 | 0.4222 |
Framework versions
- Transformers 4.47.1
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0
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Model tree for kavinda123321/speecht5_finetuned_VCTK_dataset_kavinda
Base model
microsoft/speecht5_tts