| --- |
| library_name: transformers |
| license: mit |
| base_model: microsoft/speecht5_tts |
| tags: |
| - generated_from_trainer |
| model-index: |
| - name: ASR_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. --> |
|
|
| # ASR_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: 0.4068 |
| |
| ## 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: 1000 |
| - mixed_precision_training: Native AMP |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | |
| |:-------------:|:-------:|:----:|:---------------:| |
| | 0.4993 | 3.0769 | 100 | 0.4582 | |
| | 0.463 | 6.1538 | 200 | 0.4378 | |
| | 0.4489 | 9.2308 | 300 | 0.4288 | |
| | 0.44 | 12.3077 | 400 | 0.4194 | |
| | 0.4283 | 15.3846 | 500 | 0.4168 | |
| | 0.4277 | 18.4615 | 600 | 0.4105 | |
| | 0.4248 | 21.5385 | 700 | 0.4095 | |
| | 0.4184 | 24.6154 | 800 | 0.4081 | |
| | 0.4179 | 27.6923 | 900 | 0.4065 | |
| | 0.4134 | 30.7692 | 1000 | 0.4068 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.44.2 |
| - Pytorch 2.4.1+cu121 |
| - Datasets 3.0.0 |
| - Tokenizers 0.19.1 |
| |
