metadata
license: mit
base_model: microsoft/speecht5_tts
tags:
- generated_from_trainer
model-index:
- name: speecht5_improved_data_less_steps
results: []
speecht5_improved_data_less_steps
This model is a fine-tuned version of microsoft/speecht5_tts on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.6468
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: 1e-05
- train_batch_size: 8
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 250
- training_steps: 1000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 1.4475 | 0.1533 | 25 | 1.1070 |
| 1.3754 | 0.3065 | 50 | 1.0239 |
| 1.2957 | 0.4598 | 75 | 0.9667 |
| 1.1821 | 0.6130 | 100 | 0.9231 |
| 1.1414 | 0.7663 | 125 | 0.8946 |
| 1.0555 | 0.9195 | 150 | 0.8335 |
| 0.9565 | 1.0728 | 175 | 0.7764 |
| 0.9189 | 1.2261 | 200 | 0.7485 |
| 0.8751 | 1.3793 | 225 | 0.7332 |
| 0.8533 | 1.5326 | 250 | 0.7197 |
| 0.8219 | 1.6858 | 275 | 0.7133 |
| 0.8171 | 1.8391 | 300 | 0.7009 |
| 0.8088 | 1.9923 | 325 | 0.6926 |
| 0.785 | 2.1456 | 350 | 0.6877 |
| 0.7989 | 2.2989 | 375 | 0.6824 |
| 0.7755 | 2.4521 | 400 | 0.6784 |
| 0.7914 | 2.6054 | 425 | 0.6738 |
| 0.7696 | 2.7586 | 450 | 0.6694 |
| 0.7741 | 2.9119 | 475 | 0.6680 |
| 0.7613 | 3.0651 | 500 | 0.6659 |
| 0.7733 | 3.2184 | 525 | 0.6654 |
| 0.7605 | 3.3716 | 550 | 0.6623 |
| 0.7538 | 3.5249 | 575 | 0.6606 |
| 0.7626 | 3.6782 | 600 | 0.6596 |
| 0.7573 | 3.8314 | 625 | 0.6577 |
| 0.7469 | 3.9847 | 650 | 0.6556 |
| 0.7524 | 4.1379 | 675 | 0.6537 |
| 0.7342 | 4.2912 | 700 | 0.6491 |
| 0.7305 | 4.4444 | 725 | 0.6511 |
| 0.7433 | 4.5977 | 750 | 0.6486 |
| 0.7438 | 4.7510 | 775 | 0.6487 |
| 0.7505 | 4.9042 | 800 | 0.6481 |
| 0.7354 | 5.0575 | 825 | 0.6450 |
| 0.7354 | 5.2107 | 850 | 0.6439 |
| 0.7333 | 5.3640 | 875 | 0.6462 |
| 0.7246 | 5.5172 | 900 | 0.6444 |
| 0.7289 | 5.6705 | 925 | 0.6417 |
| 0.7436 | 5.8238 | 950 | 0.6474 |
| 0.741 | 5.9770 | 975 | 0.6428 |
| 0.7443 | 6.1303 | 1000 | 0.6468 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.1.2
- Datasets 2.17.0
- Tokenizers 0.19.1