tawheed-tariq/speecht5_tts

SpeechT5 using custom dataset

This model is a fine-tuned version of microsoft/speecht5_tts on the technical_tts dataset. It achieves the following results on the evaluation set:

• Loss: nan

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: 8
• seed: 42
• gradient_accumulation_steps: 2
• total_train_batch_size: 32
• optimizer: Use 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: 4000
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss
1.7065	666.6667	1000	nan
1.4393	1333.3333	2000	nan
1.2369	2000.0	3000	nan
1.1759	2666.6667	4000	nan

Framework versions

• Transformers 4.47.0.dev0
• Pytorch 2.5.0+cu121
• Datasets 3.0.2
• Tokenizers 0.20.1