---
library_name: transformers
license: mit
base_model: microsoft/speecht5_tts
tags:
- generated_from_trainer
model-index:
- name: speecht5_finetuned_ugspeech_ak
  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_finetuned_ugspeech_ak

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: 0.3654

## 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: 0.0001
- train_batch_size: 4
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 32
- 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
- lr_scheduler_warmup_steps: 500
- training_steps: 5000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss |
|:-------------:|:-------:|:----:|:---------------:|
| 0.4378        | 1.4744  | 500  | 0.4069          |
| 0.4306        | 2.9488  | 1000 | 0.3975          |
| 0.4141        | 4.4231  | 1500 | 0.3862          |
| 0.4082        | 5.8975  | 2000 | 0.3851          |
| 0.4029        | 7.3738  | 2500 | 0.3819          |
| 0.4021        | 8.8481  | 3000 | 0.3795          |
| 0.4016        | 11.4744 | 3500 | 0.3763          |
| 0.3918        | 13.1131 | 4000 | 0.3745          |
| 0.3889        | 13.2735 | 4500 | 0.3682          |
| 0.3886        | 14.7479 | 5000 | 0.3654          |


### Framework versions

- Transformers 4.46.2
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3