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--- |
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library_name: transformers |
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license: mit |
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base_model: MBZUAI/speecht5_tts_clartts_ar |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: Arabictts |
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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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# Arabictts |
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This model is a fine-tuned version of [MBZUAI/speecht5_tts_clartts_ar](https://huggingface.co/MBZUAI/speecht5_tts_clartts_ar) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5481 |
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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: 900 |
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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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| 0.6582 | 3.7736 | 50 | 0.5892 | |
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| 0.603 | 7.5472 | 100 | 0.5603 | |
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| 0.5828 | 11.3208 | 150 | 0.5545 | |
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| 0.566 | 15.0943 | 200 | 0.5418 | |
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| 0.5504 | 18.8679 | 250 | 0.5393 | |
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| 0.5379 | 22.6415 | 300 | 0.5357 | |
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| 0.534 | 26.4151 | 350 | 0.5347 | |
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| 0.5226 | 30.1887 | 400 | 0.5352 | |
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| 0.5159 | 33.9623 | 450 | 0.5335 | |
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| 0.5058 | 37.7358 | 500 | 0.5350 | |
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| 0.5048 | 41.5094 | 550 | 0.5356 | |
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| 0.4994 | 45.2830 | 600 | 0.5367 | |
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| 0.4939 | 49.0566 | 650 | 0.5370 | |
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| 0.4923 | 52.8302 | 700 | 0.5366 | |
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| 0.488 | 56.6038 | 750 | 0.5397 | |
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| 0.4841 | 60.3774 | 800 | 0.5401 | |
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| 0.4834 | 64.1509 | 850 | 0.5490 | |
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| 0.4794 | 67.9245 | 900 | 0.5481 | |
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### Framework versions |
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- Transformers 4.46.2 |
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- Pytorch 2.5.1+cu121 |
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- Datasets 3.1.0 |
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- Tokenizers 0.20.3 |
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