---
license: mit
base_model: microsoft/speecht5_tts
tags:
- generated_from_trainer
model-index:
- name: speecht5_allvoices
  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. -->

# speecht5_allvoices

This model is a fine-tuned version of [microsoft/speecht5_tts](https://huggingface.co/microsoft/speecht5_tts) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4390

## 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: 1e-05
- train_batch_size: 4
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 10000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss |
|:-------------:|:-----:|:-----:|:---------------:|
| 0.5406        | 0.69  | 1000  | 0.5013          |
| 0.5066        | 1.39  | 2000  | 0.4761          |
| 0.4932        | 2.08  | 3000  | 0.4670          |
| 0.483         | 2.77  | 4000  | 0.4551          |
| 0.4698        | 3.47  | 5000  | 0.4507          |
| 0.4726        | 4.16  | 6000  | 0.4461          |
| 0.4685        | 4.85  | 7000  | 0.4426          |
| 0.4746        | 5.54  | 8000  | 0.4413          |
| 0.4689        | 6.24  | 9000  | 0.4418          |
| 0.4638        | 6.93  | 10000 | 0.4390          |


### Framework versions

- Transformers 4.39.0.dev0
- Pytorch 2.2.1
- Datasets 2.18.0
- Tokenizers 0.15.2