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---
license: mit
base_model: microsoft/speecht5_tts
tags:
- generated_from_trainer
datasets:
- facebook/voxpopuli
tasks:
- text-to-speech
model-index:
- name: speecht5_tts-ft-voxpopuli-it
results:
- task:
name: Text To Speech
type: text-to-speech
dataset:
name: facebook/voxpopuli
type: facebook/voxpopuli
config: it
split: train
args: it
metrics:
- name: N.A.
type: N.A.
value: N.A.
language:
- it
---
# speecht5_tts-ft-voxpopuli-it
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: 0.5126
## Model description
It uses the speaker embedding model speechbrain/spkrec-xvect-voxceleb
## Intended uses & limitations
More information needed
## Training and evaluation data
test_size=0.15
## Training procedure
### 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: 4
- 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: 300
- training_steps: 1000
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.6118 | 1.94 | 300 | 0.5508 |
| 0.5729 | 3.89 | 600 | 0.5204 |
| 0.563 | 5.83 | 900 | 0.5126 |
### Framework versions
- Transformers 4.33.0
- Pytorch 1.12.1+cu116
- Datasets 2.14.4
- Tokenizers 0.12.1 |