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---
library_name: transformers
license: mit
base_model: microsoft/speecht5_tts
tags:
- generated_from_trainer
model-index:
- name: speecht5_mehdi_new_as_try111
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_new_as_try111
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: 0.5467
## 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-06
- 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: 3000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-------:|:----:|:---------------:|
| 1.0666 | 1.7778 | 100 | 0.8627 |
| 0.8711 | 3.5556 | 200 | 0.7175 |
| 0.8314 | 5.3333 | 300 | 0.6804 |
| 0.8011 | 7.1111 | 400 | 0.6603 |
| 0.7676 | 8.8889 | 500 | 0.6402 |
| 0.7335 | 10.6667 | 600 | 0.6158 |
| 0.7093 | 12.4444 | 700 | 0.5889 |
| 0.676 | 14.2222 | 800 | 0.5793 |
| 0.6617 | 16.0 | 900 | 0.5743 |
| 0.664 | 17.7778 | 1000 | 0.5711 |
| 0.6516 | 19.5556 | 1100 | 0.5664 |
| 0.6478 | 21.3333 | 1200 | 0.5609 |
| 0.6445 | 23.1111 | 1300 | 0.5590 |
| 0.642 | 24.8889 | 1400 | 0.5601 |
| 0.6341 | 26.6667 | 1500 | 0.5585 |
| 0.6415 | 28.4444 | 1600 | 0.5584 |
| 0.6373 | 30.2222 | 1700 | 0.5533 |
| 0.6257 | 32.0 | 1800 | 0.5508 |
| 0.6311 | 33.7778 | 1900 | 0.5516 |
| 0.6201 | 35.5556 | 2000 | 0.5487 |
| 0.6257 | 37.3333 | 2100 | 0.5496 |
| 0.6304 | 39.1111 | 2200 | 0.5494 |
| 0.6177 | 40.8889 | 2300 | 0.5473 |
| 0.6235 | 42.6667 | 2400 | 0.5463 |
| 0.6202 | 44.4444 | 2500 | 0.5475 |
| 0.6191 | 46.2222 | 2600 | 0.5464 |
| 0.6188 | 48.0 | 2700 | 0.5442 |
| 0.6034 | 49.7778 | 2800 | 0.5452 |
| 0.6132 | 51.5556 | 2900 | 0.5453 |
| 0.6205 | 53.3333 | 3000 | 0.5467 |
### Framework versions
- Transformers 4.46.3
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.20.3
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