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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_feniks |
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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_feniks |
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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: 0.5319 |
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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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| 0.4478 | 3.0418 | 100 | 0.4543 | |
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| 0.4534 | 6.0837 | 200 | 0.4621 | |
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| 0.4373 | 9.1255 | 300 | 0.4543 | |
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| 0.4224 | 12.1673 | 400 | 0.4494 | |
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| 0.4127 | 15.2091 | 500 | 0.4657 | |
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| 0.4134 | 18.2510 | 600 | 0.4529 | |
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| 0.4047 | 21.2928 | 700 | 0.4724 | |
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| 0.3932 | 24.3346 | 800 | 0.4777 | |
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| 0.3907 | 27.3764 | 900 | 0.4942 | |
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| 0.3855 | 30.4183 | 1000 | 0.4870 | |
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| 0.3783 | 33.4601 | 1100 | 0.4860 | |
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| 0.3794 | 36.5019 | 1200 | 0.4867 | |
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| 0.3704 | 39.5437 | 1300 | 0.4965 | |
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| 0.3687 | 42.5856 | 1400 | 0.5151 | |
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| 0.3674 | 45.6274 | 1500 | 0.5165 | |
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| 0.3618 | 48.6692 | 1600 | 0.5377 | |
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| 0.3536 | 51.7110 | 1700 | 0.5206 | |
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| 0.3621 | 54.7529 | 1800 | 0.5419 | |
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| 0.3533 | 57.7947 | 1900 | 0.5337 | |
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| 0.3513 | 60.8365 | 2000 | 0.5319 | |
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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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