---
license: mit
base_model: microsoft/speecht5_tts
tags:
- generated_from_trainer
model-index:
- name: v1
  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. -->

# v1

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: 0.4063

## 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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 900
- num_epochs: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss |
|:-------------:|:-----:|:-----:|:---------------:|
| 0.4758        | 0.51  | 1000  | 0.4393          |
| 0.4714        | 1.02  | 2000  | 0.4303          |
| 0.4673        | 1.54  | 3000  | 0.4272          |
| 0.4646        | 2.05  | 4000  | 0.4206          |
| 0.4509        | 2.56  | 5000  | 0.4197          |
| 0.4542        | 3.07  | 6000  | 0.4162          |
| 0.4526        | 3.59  | 7000  | 0.4153          |
| 0.4484        | 4.1   | 8000  | 0.4134          |
| 0.4539        | 4.61  | 9000  | 0.4134          |
| 0.4467        | 5.12  | 10000 | 0.4111          |
| 0.4465        | 5.64  | 11000 | 0.4112          |
| 0.4424        | 6.15  | 12000 | 0.4091          |
| 0.4422        | 6.66  | 13000 | 0.4079          |
| 0.4532        | 7.17  | 14000 | 0.4084          |
| 0.447         | 7.69  | 15000 | 0.4074          |
| 0.4398        | 8.2   | 16000 | 0.4069          |
| 0.4386        | 8.71  | 17000 | 0.4068          |
| 0.4379        | 9.22  | 18000 | 0.4069          |
| 0.4345        | 9.74  | 19000 | 0.4063          |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2