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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_le4_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_le4_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: 0.4050 |
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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: 16 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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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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| 0.4561 | 19.8020 | 500 | 0.4151 | |
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| 0.4179 | 39.6040 | 1000 | 0.3994 | |
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| 0.4075 | 59.4059 | 1500 | 0.4018 | |
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| 0.3981 | 79.2079 | 2000 | 0.4029 | |
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| 0.3862 | 99.0099 | 2500 | 0.3978 | |
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| 0.3726 | 118.8119 | 3000 | 0.3978 | |
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| 0.365 | 138.6139 | 3500 | 0.3960 | |
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| 0.3525 | 158.4158 | 4000 | 0.3969 | |
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| 0.3545 | 178.2178 | 4500 | 0.3982 | |
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| 0.3473 | 198.0198 | 5000 | 0.4039 | |
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| 0.3439 | 217.8218 | 5500 | 0.4020 | |
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| 0.3371 | 237.6238 | 6000 | 0.4044 | |
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| 0.3362 | 257.4257 | 6500 | 0.4041 | |
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| 0.3311 | 277.2277 | 7000 | 0.4022 | |
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| 0.3345 | 297.0297 | 7500 | 0.4051 | |
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| 0.3348 | 316.8317 | 8000 | 0.4050 | |
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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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