---
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