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--- |
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language: |
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- ara |
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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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datasets: |
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- Arbi-Houssem/Tunisian_dataset_STT-TTS15s_filtred1.0_Mixed |
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model-index: |
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- name: SpeechT5 TTS Tunisien |
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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 TTS Tunisien |
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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 the Tunisian_dataset_STT-TTS15s_filtred1.0_Mixed dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4403 |
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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: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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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: 500 |
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- training_steps: 10000 |
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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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| 0.6355 | 6.6667 | 500 | 0.5657 | |
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| 0.5548 | 13.3333 | 1000 | 0.5314 | |
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| 0.539 | 20.0 | 1500 | 0.5286 | |
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| 0.5475 | 26.6667 | 2000 | 0.5220 | |
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| 0.5031 | 33.3333 | 2500 | 0.5193 | |
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| 0.5077 | 40.0 | 3000 | 0.5174 | |
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| 0.4724 | 46.6667 | 3500 | 0.4577 | |
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| 0.54 | 53.3333 | 4000 | 0.4610 | |
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| 0.5289 | 60.0 | 4500 | 0.4431 | |
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| 0.53 | 66.6667 | 5000 | 0.4414 | |
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| 0.5029 | 73.3333 | 5500 | 0.4404 | |
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| 0.4944 | 80.0 | 6000 | 0.4406 | |
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| 0.508 | 86.6667 | 6500 | 0.4385 | |
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| 0.5019 | 93.3333 | 7000 | 0.4410 | |
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| 0.4639 | 100.0 | 7500 | 0.4394 | |
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| 0.4918 | 106.6667 | 8000 | 0.4408 | |
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| 0.4914 | 113.3333 | 8500 | 0.4401 | |
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| 0.4747 | 120.0 | 9000 | 0.4413 | |
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| 0.4886 | 126.6667 | 9500 | 0.4409 | |
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| 0.4504 | 133.3333 | 10000 | 0.4403 | |
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### Framework versions |
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- Transformers 4.41.2 |
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- Pytorch 2.3.1+cu121 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
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