| --- |
| library_name: transformers |
| license: mit |
| base_model: MehdiAslam/speecht5_Mehdi_Final_Model |
| tags: |
| - generated_from_trainer |
| model-index: |
| - name: speecht5_Mehdi_Final_Model_2nd |
| 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. --> |
|
|
| # speecht5_Mehdi_Final_Model_2nd |
|
|
| This model is a fine-tuned version of [MehdiAslam/speecht5_Mehdi_Final_Model](https://huggingface.co/MehdiAslam/speecht5_Mehdi_Final_Model) on an unknown dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.4152 |
|
|
| ## 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-05 |
| - train_batch_size: 4 |
| - eval_batch_size: 2 |
| - seed: 42 |
| - gradient_accumulation_steps: 8 |
| - total_train_batch_size: 32 |
| - optimizer: Use OptimizerNames.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: 200 |
| - training_steps: 3000 |
| - mixed_precision_training: Native AMP |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | |
| |:-------------:|:-------:|:----:|:---------------:| |
| | 0.3962 | 3.2924 | 250 | 0.4002 | |
| | 0.3925 | 6.5847 | 500 | 0.4058 | |
| | 0.3924 | 9.8771 | 750 | 0.4070 | |
| | 0.3851 | 13.1595 | 1000 | 0.4048 | |
| | 0.3803 | 16.4518 | 1250 | 0.4059 | |
| | 0.3829 | 19.7442 | 1500 | 0.4059 | |
| | 0.3774 | 23.0266 | 1750 | 0.4034 | |
| | 0.3723 | 26.3189 | 2000 | 0.4096 | |
| | 0.3706 | 29.6113 | 2250 | 0.4122 | |
| | 0.3789 | 32.9037 | 2500 | 0.4171 | |
| | 0.3688 | 36.1860 | 2750 | 0.4156 | |
| | 0.3721 | 39.4784 | 3000 | 0.4152 | |
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|
| ### Framework versions |
|
|
| - Transformers 4.52.2 |
| - Pytorch 2.6.0+cu124 |
| - Datasets 2.14.4 |
| - Tokenizers 0.21.1 |
|
|
