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---
language:
- it
license: mit
tags:
- generated_from_trainer
datasets:
- facebook/voxpopuli
pipeline_tag: text-to-speech
base_model: microsoft/speecht5_tts
model-index:
- name: SpeechT5-it
results:
- task:
type: text-to-speech
name: Text to Speech
dataset:
name: VOXPOPULI
type: facebook/voxpopuli
config: it
split: validation
args: it
metrics:
- type: loss
value: 0.46
name: Loss
---
<!-- 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-it
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: 0.4600
## 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: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 40
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:-----:|:---------------:|
| 0.5641 | 1.0 | 712 | 0.5090 |
| 0.5394 | 2.0 | 1424 | 0.4915 |
| 0.5277 | 3.0 | 2136 | 0.4819 |
| 0.5136 | 4.0 | 2848 | 0.4798 |
| 0.5109 | 5.0 | 3560 | 0.4733 |
| 0.5078 | 6.0 | 4272 | 0.4731 |
| 0.5033 | 7.0 | 4984 | 0.4692 |
| 0.5021 | 8.0 | 5696 | 0.4691 |
| 0.4984 | 9.0 | 6408 | 0.4670 |
| 0.488 | 10.0 | 7120 | 0.4641 |
| 0.491 | 11.0 | 7832 | 0.4641 |
| 0.4918 | 12.0 | 8544 | 0.4647 |
| 0.4933 | 13.0 | 9256 | 0.4622 |
| 0.499 | 14.0 | 9968 | 0.4619 |
| 0.4906 | 15.0 | 10680 | 0.4608 |
| 0.4884 | 16.0 | 11392 | 0.4622 |
| 0.4847 | 17.0 | 12104 | 0.4616 |
| 0.4916 | 18.0 | 12816 | 0.4592 |
| 0.4845 | 19.0 | 13528 | 0.4600 |
| 0.4788 | 20.0 | 14240 | 0.4594 |
| 0.4746 | 21.0 | 14952 | 0.4607 |
| 0.4875 | 22.0 | 15664 | 0.4615 |
| 0.4831 | 23.0 | 16376 | 0.4597 |
| 0.4798 | 24.0 | 17088 | 0.4595 |
| 0.4727 | 25.0 | 17800 | 0.4592 |
| 0.4736 | 26.0 | 18512 | 0.4598 |
| 0.4746 | 27.0 | 19224 | 0.4608 |
| 0.4728 | 28.0 | 19936 | 0.4589 |
| 0.4771 | 29.0 | 20648 | 0.4593 |
| 0.4743 | 30.0 | 21360 | 0.4588 |
| 0.4785 | 31.0 | 22072 | 0.4601 |
| 0.4757 | 32.0 | 22784 | 0.4597 |
| 0.4731 | 33.0 | 23496 | 0.4598 |
| 0.4746 | 34.0 | 24208 | 0.4593 |
| 0.4715 | 35.0 | 24920 | 0.4599 |
| 0.4769 | 36.0 | 25632 | 0.4622 |
| 0.4778 | 37.0 | 26344 | 0.4605 |
| 0.4798 | 38.0 | 27056 | 0.4594 |
| 0.4694 | 39.0 | 27768 | 0.4607 |
| 0.468 | 40.0 | 28480 | 0.4600 |
### Framework versions
- Transformers 4.30.0.dev0
- Pytorch 2.0.1+cu117
- Datasets 2.13.1
- Tokenizers 0.13.3
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