---
license: mit
base_model: microsoft/speecht5_tts
tags:
- generated_from_trainer
model-index:
- name: UAE1k
  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. -->

# UAE1k

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: 0.4901

## 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: 2
- 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: 1000
- training_steps: 2500
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.5308        | 4.08  | 200  | 0.4912          |
| 0.5091        | 8.16  | 400  | 0.4925          |
| 0.4987        | 12.24 | 600  | 0.4895          |
| 0.5085        | 16.33 | 800  | 0.4896          |
| 0.5055        | 20.41 | 1000 | 0.4894          |
| 0.4941        | 24.49 | 1200 | 0.4972          |
| 0.4833        | 28.57 | 1400 | 0.4888          |
| 0.4963        | 32.65 | 1600 | 0.4916          |
| 0.4803        | 36.73 | 1800 | 0.4906          |
| 0.4918        | 40.82 | 2000 | 0.4904          |
| 0.4765        | 44.9  | 2200 | 0.4886          |
| 0.4782        | 48.98 | 2400 | 0.4901          |


### Framework versions

- Transformers 4.39.3
- Pytorch 2.3.0+cu118
- Datasets 3.0.0
- Tokenizers 0.15.2