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---
language:
- ara
license: mit
base_model: MBZUAI/speecht5_tts_clartts_ar
tags:
- generated_from_trainer
datasets:
- Arbi-Houssem/Tunisian_dataset_STT-TTS15s_filtred1.0_Mixed
model-index:
- name: SpeechT5 TTS Tunisien
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 TTS Tunisien
This model is a fine-tuned version of [MBZUAI/speecht5_tts_clartts_ar](https://huggingface.co/MBZUAI/speecht5_tts_clartts_ar) on the Tunisian_dataset_STT-TTS15s_filtred1.0_Mixed dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4403
## 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: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 10000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:--------:|:-----:|:---------------:|
| 0.6355 | 6.6667 | 500 | 0.5657 |
| 0.5548 | 13.3333 | 1000 | 0.5314 |
| 0.539 | 20.0 | 1500 | 0.5286 |
| 0.5475 | 26.6667 | 2000 | 0.5220 |
| 0.5031 | 33.3333 | 2500 | 0.5193 |
| 0.5077 | 40.0 | 3000 | 0.5174 |
| 0.4724 | 46.6667 | 3500 | 0.4577 |
| 0.54 | 53.3333 | 4000 | 0.4610 |
| 0.5289 | 60.0 | 4500 | 0.4431 |
| 0.53 | 66.6667 | 5000 | 0.4414 |
| 0.5029 | 73.3333 | 5500 | 0.4404 |
| 0.4944 | 80.0 | 6000 | 0.4406 |
| 0.508 | 86.6667 | 6500 | 0.4385 |
| 0.5019 | 93.3333 | 7000 | 0.4410 |
| 0.4639 | 100.0 | 7500 | 0.4394 |
| 0.4918 | 106.6667 | 8000 | 0.4408 |
| 0.4914 | 113.3333 | 8500 | 0.4401 |
| 0.4747 | 120.0 | 9000 | 0.4413 |
| 0.4886 | 126.6667 | 9500 | 0.4409 |
| 0.4504 | 133.3333 | 10000 | 0.4403 |
### Framework versions
- Transformers 4.41.2
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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