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--- |
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library_name: transformers |
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license: mit |
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base_model: microsoft/speecht5_tts |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: bhojpuri_tts |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# bhojpuri_tts |
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This model is a fine-tuned version of [microsoft/speecht5_tts](https://huggingface.co/microsoft/speecht5_tts) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4576 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 0.0001 |
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- train_batch_size: 4 |
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- eval_batch_size: 2 |
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- seed: 42 |
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- gradient_accumulation_steps: 8 |
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- total_train_batch_size: 32 |
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- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_steps: 100 |
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- training_steps: 6000 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:----:|:---------------:| |
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| 0.6508 | 2.5 | 200 | 0.5943 | |
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| 0.5656 | 5.0 | 400 | 0.5341 | |
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| 0.523 | 7.5 | 600 | 0.5141 | |
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| 0.512 | 10.0 | 800 | 0.4860 | |
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| 0.4966 | 12.5 | 1000 | 0.4803 | |
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| 0.522 | 15.0 | 1200 | 0.4921 | |
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| 0.4775 | 17.5 | 1400 | 0.4678 | |
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| 0.4726 | 20.0 | 1600 | 0.5031 | |
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| 0.4623 | 22.5 | 1800 | 0.4611 | |
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| 0.4612 | 25.0 | 2000 | 0.4593 | |
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| 0.4526 | 27.5 | 2200 | 0.4753 | |
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| 0.4558 | 30.0 | 2400 | 0.4578 | |
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| 0.4468 | 32.5 | 2600 | 0.4620 | |
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| 0.4474 | 35.0 | 2800 | 0.4618 | |
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| 0.4394 | 37.5 | 3000 | 0.4589 | |
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| 0.4332 | 40.0 | 3200 | 0.4463 | |
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| 0.4382 | 42.5 | 3400 | 0.4456 | |
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| 0.4382 | 45.0 | 3600 | 0.4481 | |
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| 0.4283 | 47.5 | 3800 | 0.4435 | |
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| 0.4278 | 50.0 | 4000 | 0.4470 | |
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| 0.4281 | 52.5 | 4200 | 0.4484 | |
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| 0.4236 | 55.0 | 4400 | 0.4482 | |
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| 0.422 | 57.5 | 4600 | 0.4480 | |
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| 0.4271 | 60.0 | 4800 | 0.4477 | |
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| 0.4105 | 62.5 | 5000 | 0.4475 | |
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| 0.4121 | 65.0 | 5200 | 0.4502 | |
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| 0.4115 | 67.5 | 5400 | 0.4522 | |
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| 0.4081 | 70.0 | 5600 | 0.4561 | |
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| 0.4059 | 72.5 | 5800 | 0.4610 | |
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| 0.4048 | 75.0 | 6000 | 0.4576 | |
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### Framework versions |
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- Transformers 4.51.1 |
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- Pytorch 2.6.0+cu124 |
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- Datasets 3.5.0 |
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- Tokenizers 0.21.1 |
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