urdu_text_to_speech_tts
This model is a fine-tuned version of microsoft/speecht5_tts on an common_voice_17_0 urdu dataset with very small amount. It's trained using only 4200 sentences, for business use model need to be trained on large datasets. It achieves the following results on the evaluation set:
- Loss: 0.4936
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: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 20
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.6365 | 1.0 | 486 | 0.5707 |
| 0.6045 | 2.0 | 972 | 0.5319 |
| 0.591 | 3.0 | 1458 | 0.5265 |
| 0.5711 | 4.0 | 1944 | 0.5178 |
| 0.5528 | 5.0 | 2430 | 0.5142 |
| 0.5335 | 6.0 | 2916 | 0.5073 |
| 0.5316 | 7.0 | 3402 | 0.5015 |
| 0.5308 | 8.0 | 3888 | 0.4992 |
| 0.5381 | 9.0 | 4374 | 0.5022 |
| 0.5292 | 10.0 | 4860 | 0.4977 |
| 0.5242 | 11.0 | 5346 | 0.4975 |
| 0.5129 | 12.0 | 5832 | 0.4970 |
| 0.5122 | 13.0 | 6318 | 0.4937 |
| 0.5329 | 14.0 | 6804 | 0.4943 |
| 0.5189 | 15.0 | 7290 | 0.4921 |
| 0.5164 | 16.0 | 7776 | 0.4946 |
| 0.5097 | 17.0 | 8262 | 0.4931 |
| 0.5858 | 18.0 | 8748 | 0.4948 |
| 0.5128 | 19.0 | 9234 | 0.4936 |
| 0.5203 | 20.0 | 9720 | 0.4936 |
Framework versions
- Transformers 4.42.3
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1