| --- |
| library_name: transformers |
| license: mit |
| base_model: microsoft/speecht5_tts |
| tags: |
| - generated_from_trainer |
| model-index: |
| - name: ESP_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. --> |
|
|
| # ESP_Model |
| |
| 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: 0.4896 |
| |
| ## 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: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - 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 | |
| |:-------------:|:--------:|:----:|:---------------:| |
| | 0.5777 | 11.1111 | 100 | 0.5336 | |
| | 0.5385 | 22.2222 | 200 | 0.5073 | |
| | 0.5054 | 33.3333 | 300 | 0.5005 | |
| | 0.4953 | 44.4444 | 400 | 0.4983 | |
| | 0.4714 | 55.5556 | 500 | 0.4939 | |
| | 0.4662 | 66.6667 | 600 | 0.4946 | |
| | 0.4563 | 77.7778 | 700 | 0.4981 | |
| | 0.4451 | 88.8889 | 800 | 0.4921 | |
| | 0.4412 | 100.0 | 900 | 0.4946 | |
| | 0.4384 | 111.1111 | 1000 | 0.4868 | |
| | 0.4308 | 122.2222 | 1100 | 0.4946 | |
| | 0.4226 | 133.3333 | 1200 | 0.4924 | |
| | 0.4186 | 144.4444 | 1300 | 0.4936 | |
| | 0.4205 | 155.5556 | 1400 | 0.4891 | |
| | 0.418 | 166.6667 | 1500 | 0.4896 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.46.0.dev0 |
| - Pytorch 2.4.1+cu121 |
| - Datasets 3.0.1 |
| - Tokenizers 0.20.0 |
| |
