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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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datasets: |
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- mozilla-foundation/common_voice_17_0 |
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model-index: |
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- name: Hindi_SpeechT5_finetuned |
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results: [] |
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language: |
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- hi |
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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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# Hindi_SpeechT5_finetuned |
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This model is a fine-tuned version of [microsoft/speecht5_tts](https://huggingface.co/microsoft/speecht5_tts) on the Validated split of Hindi data of [common_voice_17_0](https://huggingface.co/datasets/mozilla-foundation/common_voice_17_0) dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4524 |
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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: 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: 100 |
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- training_steps: 1500 |
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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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| 0.6856 | 0.3442 | 100 | 0.5976 | |
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| 0.5929 | 0.6885 | 200 | 0.5453 | |
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| 0.5554 | 1.0327 | 300 | 0.5130 | |
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| 0.5407 | 1.3769 | 400 | 0.5052 | |
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| 0.5318 | 1.7212 | 500 | 0.4847 | |
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| 0.5213 | 2.0654 | 600 | 0.4796 | |
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| 0.514 | 2.4096 | 700 | 0.4728 | |
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| 0.5065 | 2.7539 | 800 | 0.4703 | |
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| 0.5046 | 3.0981 | 900 | 0.4684 | |
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| 0.4976 | 3.4423 | 1000 | 0.4621 | |
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| 0.4929 | 3.7866 | 1100 | 0.4583 | |
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| 0.4791 | 4.1308 | 1200 | 0.4550 | |
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| 0.4823 | 4.4750 | 1300 | 0.4529 | |
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| 0.485 | 4.8193 | 1400 | 0.4506 | |
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| 0.4774 | 5.1635 | 1500 | 0.4524 | |
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### Framework versions |
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- Transformers 4.44.2 |
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- Pytorch 2.5.0+cu121 |
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- Datasets 3.0.2 |
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- Tokenizers 0.19.1 |
