| --- |
| library_name: transformers |
| license: mit |
| base_model: microsoft/speecht5_tts |
| tags: |
| - generated_from_trainer |
| model-index: |
| - name: The_700_data_model |
| 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. --> |
|
|
| # The_700_data_model |
| |
| 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: 0.4588 |
| |
| ## 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: 1500 |
| - mixed_precision_training: Native AMP |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | |
| |:-------------:|:-------:|:----:|:---------------:| |
| | 0.5723 | 5.1613 | 100 | 0.5148 | |
| | 0.5244 | 10.3226 | 200 | 0.4888 | |
| | 0.5008 | 15.4839 | 300 | 0.4817 | |
| | 0.4873 | 20.6452 | 400 | 0.4742 | |
| | 0.4769 | 25.8065 | 500 | 0.4700 | |
| | 0.4741 | 30.9677 | 600 | 0.4667 | |
| | 0.4612 | 36.1290 | 700 | 0.4600 | |
| | 0.4522 | 41.2903 | 800 | 0.4593 | |
| | 0.4526 | 46.4516 | 900 | 0.4601 | |
| | 0.4447 | 51.6129 | 1000 | 0.4584 | |
| | 0.4489 | 56.7742 | 1100 | 0.4604 | |
| | 0.4373 | 61.9355 | 1200 | 0.4577 | |
| | 0.4332 | 67.0968 | 1300 | 0.4592 | |
| | 0.4338 | 72.2581 | 1400 | 0.4598 | |
| | 0.4328 | 77.4194 | 1500 | 0.4588 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.46.0.dev0 |
| - Pytorch 2.4.1+cu121 |
| - Datasets 3.0.1 |
| - Tokenizers 0.20.0 |
| |
