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--- |
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library_name: transformers |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: vit_focus |
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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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# vit_focus |
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This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0599 |
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- Mse: 0.1695 |
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- Mae: 0.3672 |
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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: 3e-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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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 32 |
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- optimizer: Use OptimizerNames.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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- num_epochs: 100 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Mse | Mae | |
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|:-------------:|:-----:|:----:|:---------------:|:------:|:------:| |
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| No log | 1.0 | 2 | 0.1236 | 0.2098 | 0.4114 | |
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| No log | 2.0 | 4 | 0.1196 | 0.2083 | 0.4100 | |
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| No log | 3.0 | 6 | 0.1133 | 0.2058 | 0.4075 | |
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| No log | 4.0 | 8 | 0.1060 | 0.2028 | 0.4042 | |
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| No log | 5.0 | 10 | 0.1033 | 0.2020 | 0.4024 | |
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| No log | 6.0 | 12 | 0.0938 | 0.1972 | 0.3968 | |
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| No log | 7.0 | 14 | 0.1082 | 0.2021 | 0.4018 | |
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| No log | 8.0 | 16 | 0.0798 | 0.1897 | 0.3890 | |
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| No log | 9.0 | 18 | 0.1011 | 0.1983 | 0.3964 | |
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| No log | 10.0 | 20 | 0.0874 | 0.1913 | 0.3888 | |
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| No log | 11.0 | 22 | 0.0687 | 0.1811 | 0.3799 | |
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| No log | 12.0 | 24 | 0.0812 | 0.1892 | 0.3876 | |
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| No log | 13.0 | 26 | 0.0704 | 0.1831 | 0.3812 | |
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| No log | 14.0 | 28 | 0.0579 | 0.1744 | 0.3713 | |
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| No log | 15.0 | 30 | 0.0678 | 0.1791 | 0.3762 | |
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| No log | 16.0 | 32 | 0.0881 | 0.1883 | 0.3863 | |
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| No log | 17.0 | 34 | 0.0960 | 0.1896 | 0.3880 | |
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| No log | 18.0 | 36 | 0.0696 | 0.1776 | 0.3753 | |
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| No log | 19.0 | 38 | 0.0576 | 0.1716 | 0.3692 | |
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| No log | 20.0 | 40 | 0.0585 | 0.1720 | 0.3697 | |
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| No log | 21.0 | 42 | 0.0710 | 0.1792 | 0.3773 | |
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| No log | 22.0 | 44 | 0.0815 | 0.1843 | 0.3829 | |
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| No log | 23.0 | 46 | 0.0686 | 0.1737 | 0.3710 | |
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| No log | 24.0 | 48 | 0.0674 | 0.1734 | 0.3704 | |
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| 0.118 | 25.0 | 50 | 0.0707 | 0.1776 | 0.3757 | |
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| 0.118 | 26.0 | 52 | 0.0753 | 0.1817 | 0.3804 | |
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| 0.118 | 27.0 | 54 | 0.0708 | 0.1787 | 0.3771 | |
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| 0.118 | 28.0 | 56 | 0.0637 | 0.1721 | 0.3699 | |
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| 0.118 | 29.0 | 58 | 0.0599 | 0.1695 | 0.3672 | |
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| 0.118 | 30.0 | 60 | 0.0627 | 0.1731 | 0.3711 | |
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| 0.118 | 31.0 | 62 | 0.0693 | 0.1786 | 0.3770 | |
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| 0.118 | 32.0 | 64 | 0.0738 | 0.1799 | 0.3781 | |
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| 0.118 | 33.0 | 66 | 0.0730 | 0.1773 | 0.3752 | |
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| 0.118 | 34.0 | 68 | 0.0684 | 0.1735 | 0.3711 | |
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| 0.118 | 35.0 | 70 | 0.0642 | 0.1702 | 0.3673 | |
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| 0.118 | 36.0 | 72 | 0.0641 | 0.1721 | 0.3694 | |
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| 0.118 | 37.0 | 74 | 0.0687 | 0.1758 | 0.3737 | |
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| 0.118 | 38.0 | 76 | 0.0739 | 0.1788 | 0.3772 | |
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| 0.118 | 39.0 | 78 | 0.0706 | 0.1765 | 0.3748 | |
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| 0.118 | 40.0 | 80 | 0.0665 | 0.1726 | 0.3704 | |
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| 0.118 | 41.0 | 82 | 0.0642 | 0.1703 | 0.3677 | |
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| 0.118 | 42.0 | 84 | 0.0659 | 0.1719 | 0.3695 | |
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| 0.118 | 43.0 | 86 | 0.0682 | 0.1743 | 0.3721 | |
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| 0.118 | 44.0 | 88 | 0.0723 | 0.1776 | 0.3759 | |
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| 0.118 | 45.0 | 90 | 0.0730 | 0.1778 | 0.3761 | |
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| 0.118 | 46.0 | 92 | 0.0738 | 0.1775 | 0.3757 | |
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| 0.118 | 47.0 | 94 | 0.0743 | 0.1770 | 0.3751 | |
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| 0.118 | 48.0 | 96 | 0.0743 | 0.1766 | 0.3747 | |
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| 0.118 | 49.0 | 98 | 0.0737 | 0.1764 | 0.3746 | |
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| 0.0449 | 50.0 | 100 | 0.0729 | 0.1760 | 0.3741 | |
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### Framework versions |
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- Transformers 4.51.3 |
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- Pytorch 2.7.0 |
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- Datasets 3.5.1 |
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- Tokenizers 0.21.1 |
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