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--- |
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library_name: transformers |
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license: mit |
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base_model: maghrane/speecht5_finetuned_marar1000 |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: speecht5_finetuned_marar2000 |
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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_finetuned_marar2000 |
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This model is a fine-tuned version of [maghrane/speecht5_finetuned_marar1000](https://huggingface.co/maghrane/speecht5_finetuned_marar1000) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4801 |
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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: 1 |
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- eval_batch_size: 1 |
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- seed: 42 |
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- gradient_accumulation_steps: 8 |
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- total_train_batch_size: 8 |
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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: 2000 |
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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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| 0.528 | 0.7976 | 100 | 0.5440 | |
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| 0.5453 | 1.5952 | 200 | 0.5655 | |
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| 0.5395 | 2.3928 | 300 | 0.5418 | |
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| 0.5421 | 3.1904 | 400 | 0.5570 | |
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| 0.5384 | 3.9880 | 500 | 0.5324 | |
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| 0.5447 | 4.7856 | 600 | 0.5454 | |
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| 0.5343 | 5.5833 | 700 | 0.5220 | |
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| 0.5165 | 6.3809 | 800 | 0.5269 | |
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| 0.5171 | 7.1785 | 900 | 0.5223 | |
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| 0.507 | 7.9761 | 1000 | 0.5227 | |
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| 0.5021 | 8.7737 | 1100 | 0.5052 | |
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| 0.4982 | 9.5713 | 1200 | 0.5081 | |
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| 0.488 | 10.3689 | 1300 | 0.5026 | |
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| 0.4787 | 11.1665 | 1400 | 0.4902 | |
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| 0.4849 | 11.9641 | 1500 | 0.4936 | |
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| 0.4778 | 12.7617 | 1600 | 0.4934 | |
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| 0.4646 | 13.5593 | 1700 | 0.4858 | |
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| 0.4615 | 14.3569 | 1800 | 0.4894 | |
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| 0.4716 | 15.1545 | 1900 | 0.4832 | |
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| 0.4607 | 15.9521 | 2000 | 0.4801 | |
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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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- Tokenizers 0.20.3 |
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