---
library_name: transformers
license: mit
base_model: microsoft/speecht5_tts
tags:
- generated_from_trainer
- text-to-speech
datasets:
- facebook/voxpopuli
model-index:
- name: speecht5_finetuned_voxpopuli_hr
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# speecht5_finetuned_voxpopuli_hr

This model is a fine-tuned version of [microsoft/speecht5_tts](https://huggingface.co/microsoft/speecht5_tts) on the facebook/voxpopuli dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5769

## 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: 1
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 8
- 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: 5
- training_steps: 100
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 0.7244        | 0.0119 | 10   | 0.6521          |
| 0.6997        | 0.0239 | 20   | 0.6255          |
| 0.5865        | 0.0358 | 30   | 0.6029          |
| 0.593         | 0.0478 | 40   | 0.5946          |
| 0.6074        | 0.0597 | 50   | 0.5896          |
| 0.5793        | 0.0717 | 60   | 0.5830          |
| 0.5679        | 0.0836 | 70   | 0.5806          |
| 0.5869        | 0.0955 | 80   | 0.5793          |
| 0.5647        | 0.1075 | 90   | 0.5777          |
| 0.5902        | 0.1194 | 100  | 0.5769          |


### Framework versions

- Transformers 4.47.0
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0