---
license: mit
tags:
- generated_from_trainer
datasets:
- voxpopuli
model-index:
- name: speecht5_finetuned_voxpopuli_nl
  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_voxpopuli_nl

This model is a fine-tuned version of [microsoft/speecht5_tts](https://huggingface.co/microsoft/speecht5_tts) on the voxpopuli dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4816

## 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: 4
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 250
- training_steps: 1000

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.8188        | 0.85  | 50   | 0.7075          |
| 0.7124        | 1.71  | 100  | 0.6201          |
| 0.6763        | 2.56  | 150  | 0.5924          |
| 0.6367        | 3.42  | 200  | 0.5586          |
| 0.576         | 4.27  | 250  | 0.5216          |
| 0.5591        | 5.13  | 300  | 0.5097          |
| 0.5457        | 5.98  | 350  | 0.5027          |
| 0.5447        | 6.84  | 400  | 0.4999          |
| 0.5413        | 7.69  | 450  | 0.4933          |
| 0.5288        | 8.55  | 500  | 0.4913          |
| 0.5231        | 9.4   | 550  | 0.4881          |
| 0.5276        | 10.26 | 600  | 0.4874          |
| 0.52          | 11.11 | 650  | 0.4848          |
| 0.5238        | 11.97 | 700  | 0.4863          |
| 0.5163        | 12.82 | 750  | 0.4848          |
| 0.5191        | 13.68 | 800  | 0.4838          |
| 0.5163        | 14.53 | 850  | 0.4828          |
| 0.5126        | 15.38 | 900  | 0.4824          |
| 0.5155        | 16.24 | 950  | 0.4836          |
| 0.5193        | 17.09 | 1000 | 0.4816          |


### Framework versions

- Transformers 4.31.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3