--- library_name: transformers license: mit base_model: microsoft/speecht5_tts tags: - generated_from_trainer datasets: - arrow model-index: - name: speecht5_sw_normal results: [] --- # speecht5_sw_normal This model is a fine-tuned version of [microsoft/speecht5_tts](https://huggingface.co/microsoft/speecht5_tts) on the arrow dataset. It achieves the following results on the evaluation set: - Loss: 0.5708 ## 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: 1e-05 - train_batch_size: 16 - eval_batch_size: 2 - seed: 42 - 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: 500 - training_steps: 2000 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:-----:|:----:|:---------------:| | 0.7131 | 2.003 | 500 | 0.6449 | | 0.6108 | 4.006 | 1000 | 0.6056 | | 0.6025 | 6.009 | 1500 | 0.5798 | | 0.6159 | 8.012 | 2000 | 0.5708 | ### Framework versions - Transformers 4.50.2 - Pytorch 2.6.0+cu124 - Datasets 3.5.0 - Tokenizers 0.21.1