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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-9 |
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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-9 |
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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: 0.6525 |
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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: 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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| 0.6188 | 1.6598 | 100 | 0.6391 | |
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| 0.5578 | 3.3195 | 200 | 0.6273 | |
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| 0.5346 | 4.9793 | 300 | 0.6454 | |
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| 0.5193 | 6.6390 | 400 | 0.6131 | |
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| 0.5011 | 8.2988 | 500 | 0.6113 | |
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| 0.5069 | 9.9585 | 600 | 0.6259 | |
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| 0.495 | 11.6183 | 700 | 0.6292 | |
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| 0.4835 | 13.2780 | 800 | 0.6238 | |
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| 0.4795 | 14.9378 | 900 | 0.6300 | |
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| 0.4747 | 16.5975 | 1000 | 0.6222 | |
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| 0.4746 | 18.2573 | 1100 | 0.6387 | |
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| 0.4683 | 19.9170 | 1200 | 0.6220 | |
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| 0.4591 | 21.5768 | 1300 | 0.6474 | |
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| 0.4593 | 23.2365 | 1400 | 0.6548 | |
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| 0.4567 | 24.8963 | 1500 | 0.6322 | |
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| 0.4529 | 26.5560 | 1600 | 0.6476 | |
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| 0.4495 | 28.2158 | 1700 | 0.6517 | |
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| 0.4477 | 29.8755 | 1800 | 0.6397 | |
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| 0.442 | 31.5353 | 1900 | 0.6557 | |
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| 0.4412 | 33.1950 | 2000 | 0.6525 | |
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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 3.0.1 |
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- Tokenizers 0.19.1 |
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