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---
library_name: transformers
license: mit
base_model: microsoft/speecht5_tts
tags:
- generated_from_trainer
model-index:
- name: uz_2301_3.01_tts
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. -->
# uz_2301_3.01_tts
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: 0.4463
## 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: 0.0003
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Use adamw_torch_fused 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: 500
- training_steps: 5000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.4585 | 10.0 | 500 | 0.4543 |
| 0.4313 | 20.0 | 1000 | 0.4337 |
| 0.4032 | 30.0 | 1500 | 0.4295 |
| 0.3679 | 40.0 | 2000 | 0.4197 |
| 0.3623 | 50.0 | 2500 | 0.4206 |
| 0.3526 | 60.0 | 3000 | 0.4166 |
| 0.3356 | 70.0 | 3500 | 0.4243 |
| 0.3273 | 80.0 | 4000 | 0.4247 |
| 0.3267 | 90.0 | 4500 | 0.4366 |
| 0.3166 | 100.0 | 5000 | 0.4463 |
### Framework versions
- Transformers 4.48.3
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0
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