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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: zlm_b64_le4_s12000 |
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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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# zlm_b64_le4_s12000 |
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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: 0.3114 |
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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: 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: 12000 |
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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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| 0.5487 | 0.4188 | 500 | 0.4746 | |
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| 0.483 | 0.8375 | 1000 | 0.4227 | |
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| 0.432 | 1.2563 | 1500 | 0.3983 | |
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| 0.429 | 1.6750 | 2000 | 0.3953 | |
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| 0.4168 | 2.0938 | 2500 | 0.3701 | |
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| 0.4021 | 2.5126 | 3000 | 0.3613 | |
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| 0.3925 | 2.9313 | 3500 | 0.3509 | |
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| 0.3839 | 3.3501 | 4000 | 0.3506 | |
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| 0.3798 | 3.7688 | 4500 | 0.3423 | |
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| 0.3693 | 4.1876 | 5000 | 0.3375 | |
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| 0.3712 | 4.6064 | 5500 | 0.3367 | |
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| 0.3668 | 5.0251 | 6000 | 0.3316 | |
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| 0.3635 | 5.4439 | 6500 | 0.3291 | |
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| 0.3543 | 5.8626 | 7000 | 0.3250 | |
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| 0.3526 | 6.2814 | 7500 | 0.3221 | |
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| 0.3525 | 6.7002 | 8000 | 0.3218 | |
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| 0.3513 | 7.1189 | 8500 | 0.3182 | |
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| 0.346 | 7.5377 | 9000 | 0.3163 | |
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| 0.3448 | 7.9564 | 9500 | 0.3162 | |
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| 0.3563 | 8.3752 | 10000 | 0.3145 | |
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| 0.3449 | 8.7940 | 10500 | 0.3126 | |
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| 0.3436 | 9.2127 | 11000 | 0.3128 | |
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| 0.3413 | 9.6315 | 11500 | 0.3121 | |
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| 0.3397 | 10.0503 | 12000 | 0.3114 | |
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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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