---
license: mit
base_model: microsoft/speecht5_tts
tags:
- generated_from_trainer
- text-to-speech
datasets:
- voxpopuli
model-index:
- name: speecht5_finetuned_voxpopuli_pl
  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_pl

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: 0.4550

## 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: 500
- training_steps: 2000

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.6954        | 0.5   | 100  | 0.6110          |
| 0.644         | 1.01  | 200  | 0.5731          |
| 0.602         | 1.51  | 300  | 0.5330          |
| 0.5524        | 2.01  | 400  | 0.4982          |
| 0.5412        | 2.51  | 500  | 0.4870          |
| 0.5256        | 3.02  | 600  | 0.4775          |
| 0.5141        | 3.52  | 700  | 0.4728          |
| 0.5125        | 4.02  | 800  | 0.4688          |
| 0.5106        | 4.52  | 900  | 0.4657          |
| 0.5037        | 5.03  | 1000 | 0.4627          |
| 0.5048        | 5.53  | 1100 | 0.4622          |
| 0.4983        | 6.03  | 1200 | 0.4583          |
| 0.4981        | 6.53  | 1300 | 0.4580          |
| 0.4942        | 7.04  | 1400 | 0.4580          |
| 0.4945        | 7.54  | 1500 | 0.4578          |
| 0.4922        | 8.04  | 1600 | 0.4568          |
| 0.4893        | 8.54  | 1700 | 0.4562          |
| 0.4948        | 9.05  | 1800 | 0.4552          |
| 0.4892        | 9.55  | 1900 | 0.4547          |
| 0.4933        | 10.05 | 2000 | 0.4550          |


### Framework versions

- Transformers 4.31.0
- Pytorch 2.0.1+cu117
- Datasets 2.14.0
- Tokenizers 0.13.3