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--- |
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library_name: transformers |
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license: apache-2.0 |
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base_model: facebook/deit-base-distilled-patch16-224 |
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tags: |
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- image-classification |
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- generated_from_trainer |
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metrics: |
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- accuracy |
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model-index: |
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- name: deit-ena24 |
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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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# deit-ena24 |
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This model is a fine-tuned version of [facebook/deit-base-distilled-patch16-224](https://huggingface.co/facebook/deit-base-distilled-patch16-224) on the ena24 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0870 |
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- Accuracy: 0.9794 |
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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: 0.0002 |
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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: 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: 2 |
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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 | Accuracy | |
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|:-------------:|:------:|:----:|:---------------:|:--------:| |
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| 1.2994 | 0.1302 | 100 | 1.0314 | 0.7092 | |
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| 0.8789 | 0.2604 | 200 | 0.6169 | 0.8328 | |
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| 0.4592 | 0.3906 | 300 | 0.5234 | 0.8298 | |
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| 0.6806 | 0.5208 | 400 | 0.5431 | 0.8489 | |
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| 0.4878 | 0.6510 | 500 | 0.3905 | 0.8855 | |
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| 0.4643 | 0.7812 | 600 | 0.3281 | 0.9092 | |
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| 0.3765 | 0.9115 | 700 | 0.2398 | 0.9290 | |
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| 0.1379 | 1.0417 | 800 | 0.1861 | 0.9412 | |
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| 0.1422 | 1.1719 | 900 | 0.1657 | 0.9527 | |
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| 0.2655 | 1.3021 | 1000 | 0.1526 | 0.9557 | |
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| 0.0304 | 1.4323 | 1100 | 0.1578 | 0.9634 | |
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| 0.072 | 1.5625 | 1200 | 0.1418 | 0.9679 | |
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| 0.2936 | 1.6927 | 1300 | 0.1003 | 0.9771 | |
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| 0.0333 | 1.8229 | 1400 | 0.0935 | 0.9794 | |
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| 0.0844 | 1.9531 | 1500 | 0.0870 | 0.9794 | |
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### Framework versions |
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- Transformers 4.51.1 |
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- Pytorch 2.6.0+cu124 |
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- Datasets 3.5.0 |
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- Tokenizers 0.21.1 |
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