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

# not_overfited_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: 0.4675

## 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 |
|:-------------:|:-------:|:----:|:---------------:|
| 0.7032        | 0.4002  | 100  | 0.5819          |
| 0.6216        | 0.8004  | 200  | 0.5350          |
| 0.5847        | 1.2041  | 300  | 0.5165          |
| 0.5625        | 1.6043  | 400  | 0.5083          |
| 0.5647        | 2.0080  | 500  | 0.5047          |
| 0.5529        | 2.4082  | 600  | 0.4992          |
| 0.5524        | 2.8084  | 700  | 0.4944          |
| 0.54          | 3.2121  | 800  | 0.4924          |
| 0.5296        | 3.6123  | 900  | 0.4879          |
| 0.5418        | 4.0160  | 1000 | 0.4858          |
| 0.5345        | 4.4162  | 1100 | 0.4862          |
| 0.5186        | 4.8164  | 1200 | 0.4817          |
| 0.5232        | 5.2201  | 1300 | 0.4819          |
| 0.5309        | 5.6203  | 1400 | 0.4820          |
| 0.5315        | 6.0240  | 1500 | 0.4793          |
| 0.5238        | 6.4242  | 1600 | 0.4771          |
| 0.5121        | 6.8244  | 1700 | 0.4769          |
| 0.5252        | 7.2281  | 1800 | 0.4755          |
| 0.5251        | 7.6283  | 1900 | 0.4758          |
| 0.5136        | 8.0320  | 2000 | 0.4721          |
| 0.5176        | 8.4322  | 2100 | 0.4729          |
| 0.5096        | 8.8324  | 2200 | 0.4746          |
| 0.5155        | 9.2361  | 2300 | 0.4729          |
| 0.5091        | 9.6363  | 2400 | 0.4699          |
| 0.5223        | 10.0400 | 2500 | 0.4707          |
| 0.5105        | 10.4402 | 2600 | 0.4695          |
| 0.5148        | 10.8404 | 2700 | 0.4689          |
| 0.5101        | 11.2441 | 2800 | 0.4694          |
| 0.5125        | 11.6443 | 2900 | 0.4690          |
| 0.5093        | 12.0480 | 3000 | 0.4686          |
| 0.5057        | 12.4482 | 3100 | 0.4671          |
| 0.5063        | 12.8484 | 3200 | 0.4693          |
| 0.5071        | 13.2521 | 3300 | 0.4669          |
| 0.5051        | 13.6523 | 3400 | 0.4685          |
| 0.5049        | 14.0560 | 3500 | 0.4660          |
| 0.5015        | 14.4562 | 3600 | 0.4679          |
| 0.5041        | 14.8564 | 3700 | 0.4663          |
| 0.5108        | 15.2601 | 3800 | 0.4678          |
| 0.5048        | 15.6603 | 3900 | 0.4680          |
| 0.508         | 16.0640 | 4000 | 0.4675          |


### Framework versions

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