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---
library_name: transformers
license: mit
base_model: microsoft/speecht5_tts
tags:
- generated_from_trainer
datasets:
- voxpopuli
model-index:
- name: speecht5_finetuned_voxpopuli_es
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_es
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: 0.4743
## 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: 1000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-------:|:----:|:---------------:|
| 0.7149 | 1.1799 | 100 | 0.6094 |
| 0.6526 | 2.3599 | 200 | 0.5722 |
| 0.5987 | 3.5398 | 300 | 0.5286 |
| 0.5604 | 4.7198 | 400 | 0.5086 |
| 0.5468 | 5.8997 | 500 | 0.4940 |
| 0.5322 | 7.0796 | 600 | 0.4859 |
| 0.5272 | 8.2596 | 700 | 0.4807 |
| 0.5245 | 9.4395 | 800 | 0.4772 |
| 0.5169 | 10.6195 | 900 | 0.4765 |
| 0.5204 | 11.7994 | 1000 | 0.4743 |
### Framework versions
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.2
- Tokenizers 0.19.1
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