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tts_hataw_v1
seywan1378/tts_hataw_v1
tts_hataw_v1 is a text-to-audio model from seywan1378. 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
- Oct 5, 2025
- Updated
- Oct 6, 2025
- SHA
- 1425806a
Base models
Datasets
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_Hataw
This model is a fine-tuned version of microsoft/speecht5_tts on the HatawTTS dataset. It achieves the following results on the evaluation set:
- Loss: 0.3476
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: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED 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: 500
- training_steps: 10000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.5165 | 0.1612 | 200 | 0.4500 |
| 0.4842 | 0.3225 | 400 | 0.4352 |
| 0.4688 | 0.4837 | 600 | 0.4178 |
| 0.4588 | 0.6449 | 800 | 0.4199 |
| 0.4427 | 0.8061 | 1000 | 0.4056 |
| 0.4483 | 0.9674 | 1200 | 0.4426 |
| 0.4347 | 1.1282 | 1400 | 0.3944 |
| 0.4266 | 1.2894 | 1600 | 0.3933 |
| 0.4311 | 1.4506 | 1800 | 0.3933 |
| 0.4198 | 1.6119 | 2000 | 0.3853 |
| 0.4129 | 1.7731 | 2200 | 0.3824 |
| 0.4255 | 1.9343 | 2400 | 0.3924 |
| 0.4137 | 2.0951 | 2600 | 0.3800 |
| 0.406 | 2.2563 | 2800 | 0.3772 |
| 0.4098 | 2.4176 | 3000 | 0.3765 |
| 0.4084 | 2.5788 | 3200 | 0.3728 |
| 0.4033 | 2.7400 | 3400 | 0.3723 |
| 0.4057 | 2.9012 | 3600 | 0.3750 |
| 0.4055 | 3.0621 | 3800 | 0.3718 |
| 0.4013 | 3.2233 | 4000 | 0.3688 |
| 0.3989 | 3.3845 | 4200 | 0.3667 |
| 0.4016 | 3.5457 | 4400 | 0.3683 |
| 0.4023 | 3.7070 | 4600 | 0.3669 |
| 0.3969 | 3.8682 | 4800 | 0.3636 |
| 0.4027 | 4.0290 | 5000 | 0.3624 |
| 0.3937 | 4.1902 | 5200 | 0.3652 |
| 0.3931 | 4.3515 | 5400 | 0.3608 |
| 0.393 | 4.5127 | 5600 | 0.3624 |
| 0.3969 | 4.6739 | 5800 | 0.3587 |
| 0.3879 | 4.8351 | 6000 | 0.3580 |
| 0.389 | 4.9964 | 6200 | 0.3582 |
| 0.3884 | 5.1572 | 6400 | 0.3565 |
| 0.3885 | 5.3184 | 6600 | 0.3574 |
| 0.3827 | 5.4796 | 6800 | 0.3618 |
| 0.3843 | 5.6409 | 7000 | 0.3532 |
| 0.3816 | 5.8021 | 7200 | 0.3543 |
| 0.3826 | 5.9633 | 7400 | 0.3555 |
| 0.3835 | 6.1241 | 7600 | 0.3532 |
| 0.3778 | 6.2854 | 7800 | 0.3520 |
| 0.3761 | 6.4466 | 8000 | 0.3506 |
| 0.3745 | 6.6078 | 8200 | 0.3504 |
| 0.3816 | 6.7690 | 8400 | 0.3500 |
| 0.3784 | 6.9303 | 8600 | 0.3502 |
| 0.3757 | 7.0911 | 8800 | 0.3500 |
| 0.3756 | 7.2523 | 9000 | 0.3492 |
| 0.3758 | 7.4135 | 9200 | 0.3488 |
| 0.3781 | 7.5748 | 9400 | 0.3505 |
| 0.375 | 7.7360 | 9600 | 0.3471 |
| 0.3796 | 7.8972 | 9800 | 0.3468 |
| 0.3975 | 8.0580 | 10000 | 0.3476 |
Framework versions
- Transformers 4.56.2
- Pytorch 2.8.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.1
- Task
- Text-to-Audio
- Library
- transformers
- Type
- speecht5
- License
- mit
- Languages
- ckb
- Created
- Oct 5, 2025
- Updated
- Oct 6, 2025