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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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- common_voice_17_0 |
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model-index: |
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- name: SpeechT5-Hausa-5 |
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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-Hausa-5 |
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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_17_0 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4702 |
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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: 200 |
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- training_steps: 2000 |
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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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| 0.6245 | 1.8476 | 100 | 0.5508 | |
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| 0.5758 | 3.6952 | 200 | 0.5566 | |
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| 0.5463 | 5.5427 | 300 | 0.5015 | |
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| 0.5299 | 7.3903 | 400 | 0.4968 | |
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| 0.5139 | 9.2379 | 500 | 0.4792 | |
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| 0.5132 | 11.0855 | 600 | 0.4823 | |
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| 0.4982 | 12.9330 | 700 | 0.4640 | |
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| 0.4889 | 14.7806 | 800 | 0.4649 | |
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| 0.4841 | 16.6282 | 900 | 0.4601 | |
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| 0.4795 | 18.4758 | 1000 | 0.4631 | |
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| 0.4779 | 20.3233 | 1100 | 0.4592 | |
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| 0.4642 | 22.1709 | 1200 | 0.4651 | |
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| 0.4618 | 24.0185 | 1300 | 0.4599 | |
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| 0.4583 | 25.8661 | 1400 | 0.4634 | |
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| 0.4584 | 27.7136 | 1500 | 0.4592 | |
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| 0.4539 | 29.5612 | 1600 | 0.4604 | |
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| 0.4498 | 31.4088 | 1700 | 0.4642 | |
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| 0.4428 | 33.2564 | 1800 | 0.4677 | |
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| 0.4517 | 35.1039 | 1900 | 0.4705 | |
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| 0.4371 | 36.9515 | 2000 | 0.4702 | |
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### Framework versions |
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- Transformers 4.44.2 |
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- Pytorch 2.4.1+cu121 |
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- Datasets 3.0.0 |
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- Tokenizers 0.19.1 |
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