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speecht5_ar_tn_1.8
Arbi-Houssem/speecht5_ar_tn_1.8
speecht5_ar_tn_1.8 is a text-to-audio model from Arbi-Houssem. Use it for the text-to-audio task on the model card, and read the license before you ship it in a product. It is set up for transformers. The card lists the license as mit.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Text-to-Audio
- Library
- transformers
- License
- mit
- Model type
- speecht5
- Access
- Public
- Created
- Jun 18, 2024
- Updated
- Jun 18, 2024
- SHA
- 832e2d19
Base models
Model card
From the Hugging Face model README
<!-- 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 on the Tunisian_dataset_STT-TTS15s_filtred1.0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.4883
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: 4
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 4000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.5165 | 34.48 | 1000 | 0.4983 |
| 0.505 | 68.97 | 2000 | 0.4893 |
| 0.4996 | 103.45 | 3000 | 0.4876 |
| 0.4968 | 137.93 | 4000 | 0.4883 |
Framework versions
- Transformers 4.35.1
- Pytorch 2.3.1+cu121
- Datasets 2.14.7
- Tokenizers 0.14.1
- Task
- Text-to-Audio
- Library
- transformers
- Type
- speecht5
- License
- mit
- Languages
- ara
- Created
- Jun 18, 2024
- Updated
- Jun 18, 2024