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--- |
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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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datasets: |
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- m-aliabbas/common_voice_urdu1 |
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model-index: |
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- name: SpeechT5 TTS urdu |
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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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# SpeechT5 TTS urdu |
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This model is a fine-tuned version of [microsoft/speecht5_tts](https://huggingface.co/microsoft/speecht5_tts) on the common_voice_urdu1 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4796 |
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## Model description |
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trianed using roman urdu, using a transliteration function normal urdu was mapped to roman urdu. |
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## Use |
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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: 1e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 32 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_steps: 300 |
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- training_steps: 10500 |
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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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| 0.5782 | 4.3103 | 500 | 0.5071 | |
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| 0.5248 | 8.6207 | 1000 | 0.4863 | |
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| 0.5125 | 12.9310 | 1500 | 0.4746 | |
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| 0.5081 | 17.2414 | 2000 | 0.4727 | |
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| 0.4967 | 21.5517 | 2500 | 0.4683 | |
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| 0.4905 | 25.8621 | 3000 | 0.4645 | |
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| 0.4794 | 30.1724 | 3500 | 0.4668 | |
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| 0.4829 | 34.4828 | 4000 | 0.4647 | |
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| 0.477 | 38.7931 | 4500 | 0.4645 | |
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| 0.4637 | 43.1034 | 5000 | 0.4710 | |
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| 0.4743 | 47.4138 | 5500 | 0.4683 | |
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| 0.4595 | 51.7241 | 6000 | 0.4695 | |
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| 0.4735 | 56.0345 | 6500 | 0.4684 | |
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| 0.4613 | 60.3448 | 7000 | 0.4724 | |
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| 0.4678 | 64.6552 | 7500 | 0.4732 | |
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| 0.4538 | 68.9655 | 8000 | 0.4723 | |
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| 0.4536 | 73.2759 | 8500 | 0.4747 | |
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| 0.4587 | 77.5862 | 9000 | 0.4740 | |
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| 0.4536 | 81.8966 | 9500 | 0.4762 | |
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| 0.4606 | 86.2069 | 10000 | 0.4768 | |
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| 0.4528 | 90.5172 | 10500 | 0.4796 | |
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### Framework versions |
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- Transformers 4.43.0.dev0 |
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- Pytorch 2.3.1+cu121 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
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