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---
license: mit
base_model: microsoft/speecht5_tts
tags:
- generated_from_trainer
datasets:
- facebook/voxpopuli
model-index:
- name: speecht5_quick_finetuned_voxpopuli_it
results: []
pipeline_tag: text-to-speech
---
<!-- 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_quick_finetuned_voxpopuli_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: 0.4879
## 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: 2500
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.5535 | 1.53 | 250 | 0.5129 |
| 0.5395 | 3.07 | 500 | 0.5065 |
| 0.5393 | 4.6 | 750 | 0.4994 |
| 0.5316 | 6.13 | 1000 | 0.4956 |
| 0.5372 | 7.66 | 1250 | 0.4919 |
| 0.53 | 9.2 | 1500 | 0.4914 |
| 0.5277 | 10.73 | 1750 | 0.4888 |
| 0.5198 | 12.26 | 2000 | 0.4896 |
| 0.5236 | 13.79 | 2250 | 0.4880 |
| 0.5209 | 15.33 | 2500 | 0.4879 |
### Framework versions
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2 |