---
library_name: transformers
license: mit
base_model: microsoft/speecht5_tts
tags:
- generated_from_trainer
datasets:
- fleurs
model-index:
- name: speecht5_finetuned_uz
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# speecht5_finetuned_uz

This model is a fine-tuned version of [microsoft/speecht5_tts](https://huggingface.co/microsoft/speecht5_tts) on the fleurs dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4840

## 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: 8
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 64
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 5000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch    | Step | Validation Loss |
|:-------------:|:--------:|:----:|:---------------:|
| 3.3727        | 24.3902  | 1000 | 0.4688          |
| 3.2448        | 48.7805  | 2000 | 0.4741          |
| 3.1413        | 73.1707  | 3000 | 0.4736          |
| 3.0824        | 97.5610  | 4000 | 0.4806          |
| 3.1047        | 121.9512 | 5000 | 0.4840          |


### Framework versions

- Transformers 4.47.1
- Pytorch 2.2.2+cu121
- Datasets 3.1.0
- Tokenizers 0.21.0