--- library_name: transformers license: mit base_model: microsoft/speecht5_tts tags: - generated_from_trainer datasets: - common_voice_17_0 model-index: - name: speecht5_finetuned_commonvoice_polish_500_10k results: [] --- # speecht5_finetuned_commonvoice_polish_500_10k This model is a fine-tuned version of [microsoft/speecht5_tts](https://huggingface.co/microsoft/speecht5_tts) on the common_voice_17_0 dataset. It achieves the following results on the evaluation set: - Loss: 0.4781 ## 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 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 | |:-------------:|:------:|:----:|:---------------:| | 0.637 | 0.3431 | 100 | 0.5519 | | 0.5881 | 0.6861 | 200 | 0.5249 | | 0.549 | 1.0292 | 300 | 0.5027 | | 0.528 | 1.3722 | 400 | 0.4843 | | 0.5161 | 1.7153 | 500 | 0.4781 | ### Framework versions - Transformers 4.46.2 - Pytorch 2.5.1+cu121 - Datasets 3.1.0 - Tokenizers 0.20.3