--- library_name: transformers license: mit base_model: microsoft/speecht5_tts tags: - generated_from_trainer model-index: - name: vc results: [] --- # vc This model is a fine-tuned version of [microsoft/speecht5_tts](https://huggingface.co/microsoft/speecht5_tts) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 0.5712 ## 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-06 - train_batch_size: 8 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 8 - total_train_batch_size: 64 - 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: 2000 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:-------:|:----:|:---------------:| | 0.9951 | 2.0851 | 50 | 0.9152 | | 0.9256 | 4.1702 | 100 | 0.8480 | | 0.9001 | 6.2553 | 150 | 0.8114 | | 0.8567 | 8.3404 | 200 | 0.7857 | | 0.8139 | 10.4255 | 250 | 0.7477 | | 0.7437 | 12.5106 | 300 | 0.6724 | | 0.6937 | 14.5957 | 350 | 0.6352 | | 0.6686 | 16.6809 | 400 | 0.6194 | | 0.6487 | 18.7660 | 450 | 0.6070 | | 0.6411 | 20.8511 | 500 | 0.6009 | | 0.643 | 22.9362 | 550 | 0.5970 | | 0.6158 | 25.0 | 600 | 0.5893 | | 0.632 | 27.0851 | 650 | 0.5871 | | 0.6152 | 29.1702 | 700 | 0.5855 | | 0.6066 | 31.2553 | 750 | 0.5833 | | 0.615 | 33.3404 | 800 | 0.5817 | | 0.6011 | 35.4255 | 850 | 0.5812 | | 0.598 | 37.5106 | 900 | 0.5788 | | 0.6023 | 39.5957 | 950 | 0.5764 | | 0.6031 | 41.6809 | 1000 | 0.5775 | | 0.5976 | 43.7660 | 1050 | 0.5764 | | 0.597 | 45.8511 | 1100 | 0.5772 | | 0.5923 | 47.9362 | 1150 | 0.5727 | | 0.5793 | 50.0 | 1200 | 0.5746 | | 0.5879 | 52.0851 | 1250 | 0.5757 | | 0.5908 | 54.1702 | 1300 | 0.5727 | | 0.5838 | 56.2553 | 1350 | 0.5745 | | 0.5852 | 58.3404 | 1400 | 0.5709 | | 0.5869 | 60.4255 | 1450 | 0.5753 | | 0.585 | 62.5106 | 1500 | 0.5720 | | 0.5875 | 64.5957 | 1550 | 0.5715 | | 0.5807 | 66.6809 | 1600 | 0.5729 | | 0.5886 | 68.7660 | 1650 | 0.5730 | | 0.5831 | 70.8511 | 1700 | 0.5753 | | 0.5812 | 72.9362 | 1750 | 0.5711 | | 0.5736 | 75.0 | 1800 | 0.5768 | | 0.5761 | 77.0851 | 1850 | 0.5735 | | 0.5767 | 79.1702 | 1900 | 0.5759 | | 0.5777 | 81.2553 | 1950 | 0.5720 | | 0.5759 | 83.3404 | 2000 | 0.5712 | ### Framework versions - Transformers 4.47.0 - Pytorch 2.5.1+cu121 - Datasets 3.3.1 - Tokenizers 0.21.0