---
library_name: transformers
license: mit
base_model: microsoft/speecht5_tts
tags:
- generated_from_trainer
datasets:
- voxpopuli/fi
model-index:
- name: speecht5_finetuned_voxpopuli_fi
  results: []
pipeline_tag: text-to-speech
---

<!-- 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_voxpopuli_fi

This model is a fine-tuned version of [microsoft/speecht5_tts](https://huggingface.co./microsoft/speecht5_tts) on the voxpopuli/fi dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4433

## 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: 10
- eval_batch_size: 2
- seed: 42
- 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: 250
- training_steps: 8000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss |
|:-------------:|:-------:|:----:|:---------------:|
| 0.5561        | 0.9107  | 500  | 0.4943          |
| 0.5229        | 1.8215  | 1000 | 0.4739          |
| 0.5055        | 2.7322  | 1500 | 0.4629          |
| 0.5021        | 3.6430  | 2000 | 0.4598          |
| 0.4925        | 4.5537  | 2500 | 0.4547          |
| 0.4875        | 5.4645  | 3000 | 0.4523          |
| 0.4797        | 6.3752  | 3500 | 0.4509          |
| 0.4778        | 7.2860  | 4000 | 0.4488          |
| 0.4732        | 8.1967  | 4500 | 0.4477          |
| 0.4759        | 9.1075  | 5000 | 0.4466          |
| 0.4908        | 10.0182 | 5500 | 0.4448          |
| 0.4817        | 10.9290 | 6000 | 0.4442          |
| 0.4784        | 11.8397 | 6500 | 0.4443          |
| 0.4775        | 12.7505 | 7000 | 0.4437          |
| 0.4717        | 13.6612 | 7500 | 0.4436          |
| 0.4744        | 14.5719 | 8000 | 0.4433          |


### Framework versions

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