Senga Nt Fused Tts

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

• learning_rate: 5e-05
• train_batch_size: 8
• eval_batch_size: 8
• seed: 3407
• gradient_accumulation_steps: 4
• total_train_batch_size: 32
• 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
• lr_scheduler_warmup_steps: 2000
• training_steps: 20000
• mixed_precision_training: Native AMP

Training results

Framework versions

• Transformers 4.57.1
• Pytorch 2.8.0+cu128
• Datasets 4.2.0
• Tokenizers 0.22.2

--- library_name: transformers license: mit base_model: microsoft/speecht5_tts tags: - generated_from_trainer model-index: - name: senga-nt-fused-tts results: [] --- <!-- 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. --> # senga-nt-fused-tts This model is a fine-tuned version of [microsoft/speecht5_tts](https://huggingface.co/microsoft/speecht5_tts) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.0868 ## 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: 5e-05 - train_batch_size: 8 - eval_batch_size: 8 - seed: 3407 - gradient_accumulation_steps: 4 - total_train_batch_size: 32 - 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 - lr_scheduler_warmup_steps: 2000 - training_steps: 20000 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:-------:|:-----:|:---------------:| | 0.1376 | 9.0499 | 2000 | 0.1013 | | 0.1242 | 18.0999 | 4000 | 0.0932 | | 0.1111 | 27.1498 | 6000 | 0.0903 | | 0.1081 | 36.1998 | 8000 | 0.0895 | | 0.1038 | 45.2497 | 10000 | 0.0889 | | 0.0995 | 54.2997 | 12000 | 0.0870 | | 0.1009 | 63.3496 | 14000 | 0.0875 | | 0.0969 | 72.3995 | 16000 | 0.0868 | | 0.0997 | 81.4495 | 18000 | 0.0871 | | 0.0962 | 90.4994 | 20000 | 0.0868 | ### Framework versions - Transformers 4.57.1 - Pytorch 2.8.0+cu128 - Datasets 4.2.0 - Tokenizers 0.22.2