Downloads · 30 days
5
2% of all-time downloads
speecht5_finetuned_kazakh_tts2_1
zizzimars/speecht5_finetuned_kazakh_tts2_1
speecht5_finetuned_kazakh_tts2_1 is a text-to-audio model from zizzimars. 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
302
Public
Parameters
144M
11.6 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
- Apr 14, 2024
- Updated
- Apr 30, 2024
- SHA
- 6e759921
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_finetuned_kazakh_tts2_1
This model is a fine-tuned version of microsoft/speecht5_tts on the KazakhTTS2 dataset (Mussakhojayeva, S., Khassanov, Y., & Varol, H.A. (2022). KazakhTTS2: Extending the Open-Source Kazakh TTS Corpus With More Data, Speakers, and Topics. International Conference on Language Resources and Evaluation). It achieves the following results on the evaluation set:
- Loss: 0.4600
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: 4
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 200
- training_steps: 2000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.725 | 0.06 | 100 | 0.6639 |
| 0.6132 | 0.11 | 200 | 0.5466 |
| 0.571 | 0.17 | 300 | 0.5207 |
| 0.5647 | 0.22 | 400 | 0.5120 |
| 0.5556 | 0.28 | 500 | 0.5047 |
| 0.5475 | 0.34 | 600 | 0.5003 |
| 0.5432 | 0.39 | 700 | 0.4975 |
| 0.5366 | 0.45 | 800 | 0.4944 |
| 0.5376 | 0.5 | 900 | 0.4913 |
| 0.5325 | 0.56 | 1000 | 0.4868 |
| 0.5281 | 0.62 | 1100 | 0.4861 |
| 0.5288 | 0.67 | 1200 | 0.4848 |
| 0.5251 | 0.73 | 1300 | 0.4825 |
| 0.5213 | 0.78 | 1400 | 0.4818 |
| 0.5225 | 0.84 | 1500 | 0.4823 |
| 0.5199 | 0.9 | 1600 | 0.4812 |
| 0.5211 | 0.95 | 1700 | 0.4816 |
| 0.5194 | 1.01 | 1800 | 0.4826 |
| 0.5224 | 1.06 | 1900 | 0.4798 |
| 0.5213 | 1.12 | 2000 | 0.4800 |
Framework versions
- Transformers 4.38.1
- Pytorch 2.2.1+cu118
- Datasets 2.18.0
- Tokenizers 0.15.2
- Task
- Text-to-Audio
- Library
- transformers
- Type
- speecht5
- License
- mit
- Created
- Apr 14, 2024
- Updated
- Apr 30, 2024