---
license: mit
tags:
- generated_from_trainer
- text-to-speech
datasets:
- voxpopuli
model-index:
- name: speecht5_finetuned_voxpopuli_Nederlands
  results: []
---

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# speecht5_finetuned_voxpopuli_Nederlands

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: 0.4888

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure
from transformers import Seq2SeqTrainer

trainer = Seq2SeqTrainer(
    args=training_args,
    model=model,
    train_dataset=dataset["train"],
    eval_dataset=dataset["test"],
    data_collator=data_collator,
    tokenizer=processor,
)

### 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: 16
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 50
- training_steps: 500

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.6266        | 1.72  | 100  | 0.5448          |
| 0.5533        | 3.44  | 200  | 0.5040          |
| 0.5401        | 5.16  | 300  | 0.4930          |
| 0.535         | 6.88  | 400  | 0.4898          |
| 0.5331        | 8.6   | 500  | 0.4888          |


### Framework versions

- Transformers 4.30.2
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.13.3