---
library_name: transformers
license: mit
base_model: MBZUAI/speecht5_tts_clartts_ar
tags:
- generated_from_trainer
model-index:
- name: ArabicTTS
  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. -->

# ArabicTTS

This model is a fine-tuned version of [MBZUAI/speecht5_tts_clartts_ar](https://huggingface.co/MBZUAI/speecht5_tts_clartts_ar) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5655

## 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 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: 100
- training_steps: 700
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch    | Step | Validation Loss |
|:-------------:|:--------:|:----:|:---------------:|
| 0.6259        | 8.1509   | 50   | 0.6030          |
| 0.5631        | 16.3019  | 100  | 0.5849          |
| 0.5468        | 24.4528  | 150  | 0.5856          |
| 0.5217        | 32.6038  | 200  | 0.5570          |
| 0.5102        | 40.7547  | 250  | 0.5555          |
| 0.4944        | 48.9057  | 300  | 0.5534          |
| 0.4829        | 57.1321  | 350  | 0.5509          |
| 0.477         | 65.2830  | 400  | 0.5567          |
| 0.4692        | 73.4340  | 450  | 0.5552          |
| 0.4635        | 81.5849  | 500  | 0.5572          |
| 0.4592        | 89.7358  | 550  | 0.5573          |
| 0.4546        | 97.8868  | 600  | 0.5610          |
| 0.4515        | 106.1132 | 650  | 0.5653          |
| 0.45          | 114.2642 | 700  | 0.5655          |


### Framework versions

- Transformers 4.46.2
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3