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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: speecht5_mehdi_as_1 |
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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_mehdi_as_1 |
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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: 0.5176 |
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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 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: 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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| 0.611 | 3.5556 | 100 | 0.5611 | |
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| 0.55 | 7.1111 | 200 | 0.5361 | |
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| 0.5435 | 10.6667 | 300 | 0.5158 | |
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| 0.5081 | 14.2222 | 400 | 0.4987 | |
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| 0.4918 | 17.7778 | 500 | 0.5124 | |
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| 0.4851 | 21.3333 | 600 | 0.4984 | |
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| 0.4783 | 24.8889 | 700 | 0.5027 | |
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| 0.4721 | 28.4444 | 800 | 0.4964 | |
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| 0.4595 | 32.0 | 900 | 0.5092 | |
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| 0.4524 | 35.5556 | 1000 | 0.5169 | |
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| 0.4528 | 39.1111 | 1100 | 0.5130 | |
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| 0.4423 | 42.6667 | 1200 | 0.5114 | |
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| 0.4401 | 46.2222 | 1300 | 0.5175 | |
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| 0.439 | 49.7778 | 1400 | 0.5202 | |
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| 0.4357 | 53.3333 | 1500 | 0.5176 | |
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### Framework versions |
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- Transformers 4.46.3 |
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- Pytorch 2.5.1+cu121 |
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- Tokenizers 0.20.3 |
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