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--- |
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license: apache-2.0 |
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base_model: facebook/deit-small-patch16-224 |
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tags: |
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- generated_from_trainer |
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datasets: |
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- imagefolder |
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metrics: |
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- accuracy |
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model-index: |
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- name: deit-small-patch16-224-finetuned-piid |
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results: |
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- task: |
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name: Image Classification |
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type: image-classification |
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dataset: |
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name: imagefolder |
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type: imagefolder |
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config: default |
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split: val |
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args: default |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.7671232876712328 |
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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-small-patch16-224-finetuned-piid |
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This model is a fine-tuned version of [facebook/deit-small-patch16-224](https://huggingface.co/facebook/deit-small-patch16-224) on the imagefolder dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6409 |
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- Accuracy: 0.7671 |
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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: 5e-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: 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_ratio: 0.1 |
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- num_epochs: 20 |
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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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| 1.2316 | 0.98 | 20 | 1.0505 | 0.5251 | |
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| 0.7423 | 2.0 | 41 | 0.7781 | 0.6347 | |
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| 0.6286 | 2.98 | 61 | 0.7165 | 0.6712 | |
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| 0.5196 | 4.0 | 82 | 0.6297 | 0.7260 | |
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| 0.4871 | 4.98 | 102 | 0.6319 | 0.7352 | |
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| 0.3666 | 6.0 | 123 | 0.5845 | 0.7443 | |
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| 0.2804 | 6.98 | 143 | 0.6830 | 0.7260 | |
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| 0.2812 | 8.0 | 164 | 0.5775 | 0.7580 | |
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| 0.2244 | 8.98 | 184 | 0.6285 | 0.7397 | |
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| 0.233 | 10.0 | 205 | 0.5887 | 0.7671 | |
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| 0.2368 | 10.98 | 225 | 0.6399 | 0.7671 | |
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| 0.1849 | 12.0 | 246 | 0.6024 | 0.7626 | |
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| 0.1877 | 12.98 | 266 | 0.5884 | 0.7763 | |
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| 0.1686 | 14.0 | 287 | 0.6725 | 0.7900 | |
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| 0.1769 | 14.98 | 307 | 0.5996 | 0.7671 | |
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| 0.1267 | 16.0 | 328 | 0.6102 | 0.7626 | |
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| 0.0933 | 16.98 | 348 | 0.6367 | 0.7854 | |
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| 0.1247 | 18.0 | 369 | 0.6364 | 0.7626 | |
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| 0.0837 | 18.98 | 389 | 0.6379 | 0.7671 | |
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| 0.1476 | 19.51 | 400 | 0.6409 | 0.7671 | |
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### Framework versions |
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- Transformers 4.35.0 |
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- Pytorch 2.1.0+cu118 |
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- Datasets 2.14.6 |
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- Tokenizers 0.14.1 |
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