---
library_name: transformers
license: mit
base_model: microsoft/speecht5_tts
tags:
- generated_from_trainer
model-index:
- name: speecht5_arabic_female_voice
  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_arabic_female_voice

This model is a fine-tuned version of [microsoft/speecht5_tts](https://huggingface.co/microsoft/speecht5_tts) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3886

## 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: 0.0001
- train_batch_size: 4
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 32
- 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: 200
- training_steps: 2000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss |
|:-------------:|:-------:|:----:|:---------------:|
| 0.5085        | 4.3360  | 200  | 0.4609          |
| 0.4697        | 8.6721  | 400  | 0.4265          |
| 0.4509        | 13.0081 | 600  | 0.4111          |
| 0.4289        | 17.3442 | 800  | 0.4057          |
| 0.4208        | 21.6802 | 1000 | 0.4049          |
| 0.4136        | 26.0163 | 1200 | 0.3990          |
| 0.4072        | 30.3523 | 1400 | 0.3980          |
| 0.4011        | 34.6883 | 1600 | 0.3920          |
| 0.3971        | 39.0244 | 1800 | 0.3905          |
| 0.3898        | 43.3604 | 2000 | 0.3886          |


### Framework versions

- Transformers 4.46.3
- Pytorch 2.10.0+cu128
- Datasets 2.19.0
- Tokenizers 0.20.3