Downloads · 30 days
42
10% of all-time downloads
SpeechT5-Hausa-7
Judah04/SpeechT5-Hausa-7
SpeechT5-Hausa-7 is a text-to-audio model from Judah04. 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. --
All-time downloads
429
Public
Parameters
144M
23.1 GB on disk
Likes
0
Public
Repo makeup
Click a slice to open those files.
.safetensors578 MB · 100%
At a glance
- Task
- Text-to-Audio
- Library
- transformers
- License
- mit
- Model type
- speecht5
- Access
- Public
- Created
- Sep 25, 2024
- Updated
- Oct 5, 2024
- SHA
- 3ef48fdf
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-Hausa-7
This model is a fine-tuned version of microsoft/speecht5_tts on the common_voice_17_0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.4703
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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- training_steps: 2000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.6092 | 1.8476 | 100 | 0.5552 |
| 0.5638 | 3.6952 | 200 | 0.5097 |
| 0.5384 | 5.5427 | 300 | 0.5010 |
| 0.527 | 7.3903 | 400 | 0.4850 |
| 0.5157 | 9.2379 | 500 | 0.4830 |
| 0.5061 | 11.0855 | 600 | 0.4727 |
| 0.4955 | 12.9330 | 700 | 0.4773 |
| 0.4855 | 14.7806 | 800 | 0.4692 |
| 0.4801 | 16.6282 | 900 | 0.4651 |
| 0.4793 | 18.4758 | 1000 | 0.4623 |
| 0.4753 | 20.3233 | 1100 | 0.4708 |
| 0.4606 | 22.1709 | 1200 | 0.4668 |
| 0.4595 | 24.0185 | 1300 | 0.4622 |
| 0.4558 | 25.8661 | 1400 | 0.4628 |
| 0.4581 | 27.7136 | 1500 | 0.4628 |
| 0.4532 | 29.5612 | 1600 | 0.4665 |
| 0.4487 | 31.4088 | 1700 | 0.4652 |
| 0.4416 | 33.2564 | 1800 | 0.4661 |
| 0.4475 | 35.1039 | 1900 | 0.4677 |
| 0.4375 | 36.9515 | 2000 | 0.4703 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.0
- Tokenizers 0.19.1
- Task
- Text-to-Audio
- Library
- transformers
- Type
- speecht5
- License
- mit
- Created
- Sep 25, 2024
- Updated
- Oct 5, 2024