---
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: 0.5481

## 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: 900
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss |
|:-------------:|:-------:|:----:|:---------------:|
| 0.6582        | 3.7736  | 50   | 0.5892          |
| 0.603         | 7.5472  | 100  | 0.5603          |
| 0.5828        | 11.3208 | 150  | 0.5545          |
| 0.566         | 15.0943 | 200  | 0.5418          |
| 0.5504        | 18.8679 | 250  | 0.5393          |
| 0.5379        | 22.6415 | 300  | 0.5357          |
| 0.534         | 26.4151 | 350  | 0.5347          |
| 0.5226        | 30.1887 | 400  | 0.5352          |
| 0.5159        | 33.9623 | 450  | 0.5335          |
| 0.5058        | 37.7358 | 500  | 0.5350          |
| 0.5048        | 41.5094 | 550  | 0.5356          |
| 0.4994        | 45.2830 | 600  | 0.5367          |
| 0.4939        | 49.0566 | 650  | 0.5370          |
| 0.4923        | 52.8302 | 700  | 0.5366          |
| 0.488         | 56.6038 | 750  | 0.5397          |
| 0.4841        | 60.3774 | 800  | 0.5401          |
| 0.4834        | 64.1509 | 850  | 0.5490          |
| 0.4794        | 67.9245 | 900  | 0.5481          |


### Framework versions

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