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--- |
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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: ceb_b64_le5_s8000 |
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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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# ceb_b64_le5_s8000 |
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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: 0.3930 |
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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: 1e-05 |
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- train_batch_size: 32 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 64 |
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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: 2000 |
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- training_steps: 8000 |
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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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| 0.5525 | 19.6078 | 500 | 0.4686 | |
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| 0.4756 | 39.2157 | 1000 | 0.4276 | |
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| 0.4543 | 58.8235 | 1500 | 0.4116 | |
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| 0.4346 | 78.4314 | 2000 | 0.4028 | |
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| 0.4292 | 98.0392 | 2500 | 0.3997 | |
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| 0.4166 | 117.6471 | 3000 | 0.3952 | |
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| 0.4122 | 137.2549 | 3500 | 0.3957 | |
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| 0.4063 | 156.8627 | 4000 | 0.3940 | |
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| 0.4028 | 176.4706 | 4500 | 0.3951 | |
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| 0.3982 | 196.0784 | 5000 | 0.3931 | |
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| 0.4055 | 215.6863 | 5500 | 0.3946 | |
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| 0.4019 | 235.2941 | 6000 | 0.3925 | |
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| 0.4 | 254.9020 | 6500 | 0.3940 | |
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| 0.4046 | 274.5098 | 7000 | 0.3953 | |
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| 0.3955 | 294.1176 | 7500 | 0.3945 | |
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| 0.3944 | 313.7255 | 8000 | 0.3930 | |
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### Framework versions |
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- Transformers 4.41.0.dev0 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.19.0 |
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- Tokenizers 0.19.1 |
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