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bhojpuri_tts
vikash06/bhojpuri_tts
bhojpuri_tts is a text-to-audio model from vikash06. 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
- Apr 16, 2025
- Updated
- Apr 19, 2025
- SHA
- f17b7c89
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. -->
bhojpuri_tts
This model is a fine-tuned version of microsoft/speecht5_tts on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.4576
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: Use OptimizerNames.ADAMW_TORCH 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: 100
- training_steps: 6000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.6508 | 2.5 | 200 | 0.5943 |
| 0.5656 | 5.0 | 400 | 0.5341 |
| 0.523 | 7.5 | 600 | 0.5141 |
| 0.512 | 10.0 | 800 | 0.4860 |
| 0.4966 | 12.5 | 1000 | 0.4803 |
| 0.522 | 15.0 | 1200 | 0.4921 |
| 0.4775 | 17.5 | 1400 | 0.4678 |
| 0.4726 | 20.0 | 1600 | 0.5031 |
| 0.4623 | 22.5 | 1800 | 0.4611 |
| 0.4612 | 25.0 | 2000 | 0.4593 |
| 0.4526 | 27.5 | 2200 | 0.4753 |
| 0.4558 | 30.0 | 2400 | 0.4578 |
| 0.4468 | 32.5 | 2600 | 0.4620 |
| 0.4474 | 35.0 | 2800 | 0.4618 |
| 0.4394 | 37.5 | 3000 | 0.4589 |
| 0.4332 | 40.0 | 3200 | 0.4463 |
| 0.4382 | 42.5 | 3400 | 0.4456 |
| 0.4382 | 45.0 | 3600 | 0.4481 |
| 0.4283 | 47.5 | 3800 | 0.4435 |
| 0.4278 | 50.0 | 4000 | 0.4470 |
| 0.4281 | 52.5 | 4200 | 0.4484 |
| 0.4236 | 55.0 | 4400 | 0.4482 |
| 0.422 | 57.5 | 4600 | 0.4480 |
| 0.4271 | 60.0 | 4800 | 0.4477 |
| 0.4105 | 62.5 | 5000 | 0.4475 |
| 0.4121 | 65.0 | 5200 | 0.4502 |
| 0.4115 | 67.5 | 5400 | 0.4522 |
| 0.4081 | 70.0 | 5600 | 0.4561 |
| 0.4059 | 72.5 | 5800 | 0.4610 |
| 0.4048 | 75.0 | 6000 | 0.4576 |
Framework versions
- Transformers 4.51.1
- Pytorch 2.6.0+cu124
- Datasets 3.5.0
- Tokenizers 0.21.1
- Task
- Text-to-Audio
- Library
- transformers
- Type
- speecht5
- License
- mit
- Created
- Apr 16, 2025
- Updated
- Apr 19, 2025