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---
library_name: transformers
license: mit
base_model: microsoft/speecht5_tts
tags:
- generated_from_trainer
model-index:
- name: last_vc
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. -->
# last_vc
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: 0.5195
## 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
- training_steps: 4000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-------:|:----:|:---------------:|
| 0.7194 | 0.3820 | 100 | 0.6257 |
| 0.6475 | 0.7641 | 200 | 0.5903 |
| 0.622 | 1.1452 | 300 | 0.5744 |
| 0.6042 | 1.5272 | 400 | 0.5645 |
| 0.5932 | 1.9093 | 500 | 0.5568 |
| 0.5962 | 2.2904 | 600 | 0.5545 |
| 0.5877 | 2.6724 | 700 | 0.5494 |
| 0.572 | 3.0535 | 800 | 0.5465 |
| 0.5705 | 3.4355 | 900 | 0.5434 |
| 0.5698 | 3.8176 | 1000 | 0.5394 |
| 0.5661 | 4.1987 | 1100 | 0.5393 |
| 0.5569 | 4.5807 | 1200 | 0.5378 |
| 0.5627 | 4.9628 | 1300 | 0.5363 |
| 0.5596 | 5.3438 | 1400 | 0.5338 |
| 0.5581 | 5.7259 | 1500 | 0.5310 |
| 0.5542 | 6.1070 | 1600 | 0.5307 |
| 0.5483 | 6.4890 | 1700 | 0.5304 |
| 0.5536 | 6.8711 | 1800 | 0.5273 |
| 0.5595 | 7.2521 | 1900 | 0.5273 |
| 0.5448 | 7.6342 | 2000 | 0.5276 |
| 0.5429 | 8.0153 | 2100 | 0.5270 |
| 0.5507 | 8.3973 | 2200 | 0.5261 |
| 0.5511 | 8.7794 | 2300 | 0.5251 |
| 0.5501 | 9.1605 | 2400 | 0.5243 |
| 0.5434 | 9.5425 | 2500 | 0.5254 |
| 0.5434 | 9.9245 | 2600 | 0.5249 |
| 0.5477 | 10.3056 | 2700 | 0.5210 |
| 0.5455 | 10.6877 | 2800 | 0.5213 |
| 0.5412 | 11.0688 | 2900 | 0.5212 |
| 0.5416 | 11.4508 | 3000 | 0.5203 |
| 0.5417 | 11.8329 | 3100 | 0.5236 |
| 0.5361 | 12.2139 | 3200 | 0.5220 |
| 0.5411 | 12.5960 | 3300 | 0.5220 |
| 0.5446 | 12.9780 | 3400 | 0.5191 |
| 0.5415 | 13.3591 | 3500 | 0.5199 |
| 0.5426 | 13.7412 | 3600 | 0.5210 |
| 0.5391 | 14.1223 | 3700 | 0.5198 |
| 0.5418 | 14.5043 | 3800 | 0.5196 |
| 0.5437 | 14.8863 | 3900 | 0.5195 |
| 0.539 | 15.2674 | 4000 | 0.5195 |
### Framework versions
- Transformers 4.47.0
- Pytorch 2.5.1+cu121
- Datasets 3.3.1
- Tokenizers 0.21.0
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