---
library_name: transformers
license: mit
base_model: microsoft/speecht5_tts
tags:
- generated_from_trainer
model-index:
- name: na_voice_clon
  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. -->

# na_voice_clon

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: 0.5806

## 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-06
- train_batch_size: 8
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 64
- 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: 500
- training_steps: 2000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss |
|:-------------:|:-------:|:----:|:---------------:|
| 0.9913        | 1.1905  | 50   | 0.8766          |
| 0.9763        | 2.3810  | 100  | 0.8198          |
| 0.9234        | 3.5714  | 150  | 0.7816          |
| 0.8756        | 4.7619  | 200  | 0.7637          |
| 0.8449        | 5.9524  | 250  | 0.7322          |
| 0.7719        | 7.1429  | 300  | 0.6737          |
| 0.7254        | 8.3333  | 350  | 0.6366          |
| 0.6845        | 9.5238  | 400  | 0.6195          |
| 0.6737        | 10.7143 | 450  | 0.6131          |
| 0.6689        | 11.9048 | 500  | 0.6178          |
| 0.6595        | 13.0952 | 550  | 0.6039          |
| 0.655         | 14.2857 | 600  | 0.6046          |
| 0.6514        | 15.4762 | 650  | 0.5944          |
| 0.6478        | 16.6667 | 700  | 0.5940          |
| 0.6327        | 17.8571 | 750  | 0.5939          |
| 0.6418        | 19.0476 | 800  | 0.5938          |
| 0.6329        | 20.2381 | 850  | 0.5887          |
| 0.6364        | 21.4286 | 900  | 0.5906          |
| 0.6284        | 22.6190 | 950  | 0.5887          |
| 0.6238        | 23.8095 | 1000 | 0.5865          |
| 0.624         | 25.0    | 1050 | 0.5859          |
| 0.6163        | 26.1905 | 1100 | 0.5845          |
| 0.6254        | 27.3810 | 1150 | 0.5840          |
| 0.6168        | 28.5714 | 1200 | 0.5831          |
| 0.6141        | 29.7619 | 1250 | 0.5791          |
| 0.614         | 30.9524 | 1300 | 0.5835          |
| 0.6121        | 32.1429 | 1350 | 0.5788          |
| 0.6227        | 33.3333 | 1400 | 0.5785          |
| 0.6198        | 34.5238 | 1450 | 0.5775          |
| 0.6142        | 35.7143 | 1500 | 0.5803          |
| 0.6183        | 36.9048 | 1550 | 0.5765          |
| 0.6161        | 38.0952 | 1600 | 0.5781          |
| 0.6061        | 39.2857 | 1650 | 0.5768          |
| 0.6167        | 40.4762 | 1700 | 0.5773          |
| 0.6063        | 41.6667 | 1750 | 0.5775          |
| 0.6107        | 42.8571 | 1800 | 0.5777          |
| 0.6084        | 44.0476 | 1850 | 0.5772          |
| 0.6074        | 45.2381 | 1900 | 0.5757          |
| 0.6023        | 46.4286 | 1950 | 0.5766          |
| 0.6077        | 47.6190 | 2000 | 0.5806          |


### Framework versions

- Transformers 4.47.0
- Pytorch 2.5.1+cu121
- Datasets 3.3.1
- Tokenizers 0.21.0