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--- |
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license: apache-2.0 |
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base_model: facebook/deit-tiny-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: smids_5x_deit_tiny_sgd_001_fold1 |
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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: test |
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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: 0.8714524207011686 |
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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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# smids_5x_deit_tiny_sgd_001_fold1 |
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This model is a fine-tuned version of [facebook/deit-tiny-patch16-224](https://huggingface.co/facebook/deit-tiny-patch16-224) on the imagefolder dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3293 |
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- Accuracy: 0.8715 |
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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: 0.001 |
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- train_batch_size: 32 |
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- eval_batch_size: 32 |
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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_ratio: 0.1 |
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- num_epochs: 50 |
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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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| 0.7747 | 1.0 | 376 | 0.8081 | 0.6327 | |
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| 0.5327 | 2.0 | 752 | 0.5949 | 0.7462 | |
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| 0.4332 | 3.0 | 1128 | 0.5030 | 0.7846 | |
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| 0.4359 | 4.0 | 1504 | 0.4457 | 0.8097 | |
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| 0.3937 | 5.0 | 1880 | 0.4107 | 0.8164 | |
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| 0.3325 | 6.0 | 2256 | 0.3873 | 0.8297 | |
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| 0.2877 | 7.0 | 2632 | 0.3645 | 0.8347 | |
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| 0.2962 | 8.0 | 3008 | 0.3585 | 0.8397 | |
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| 0.3002 | 9.0 | 3384 | 0.3450 | 0.8414 | |
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| 0.2749 | 10.0 | 3760 | 0.3357 | 0.8514 | |
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| 0.2826 | 11.0 | 4136 | 0.3303 | 0.8614 | |
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| 0.2607 | 12.0 | 4512 | 0.3246 | 0.8664 | |
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| 0.2479 | 13.0 | 4888 | 0.3195 | 0.8731 | |
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| 0.209 | 14.0 | 5264 | 0.3192 | 0.8698 | |
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| 0.2492 | 15.0 | 5640 | 0.3190 | 0.8631 | |
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| 0.2421 | 16.0 | 6016 | 0.3201 | 0.8664 | |
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| 0.2313 | 17.0 | 6392 | 0.3123 | 0.8731 | |
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| 0.2635 | 18.0 | 6768 | 0.3189 | 0.8715 | |
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| 0.22 | 19.0 | 7144 | 0.3169 | 0.8698 | |
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| 0.1933 | 20.0 | 7520 | 0.3154 | 0.8715 | |
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| 0.1972 | 21.0 | 7896 | 0.3125 | 0.8748 | |
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| 0.2184 | 22.0 | 8272 | 0.3238 | 0.8681 | |
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| 0.2395 | 23.0 | 8648 | 0.3208 | 0.8715 | |
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| 0.2148 | 24.0 | 9024 | 0.3152 | 0.8681 | |
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| 0.2046 | 25.0 | 9400 | 0.3215 | 0.8698 | |
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| 0.2137 | 26.0 | 9776 | 0.3154 | 0.8681 | |
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| 0.1523 | 27.0 | 10152 | 0.3167 | 0.8731 | |
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| 0.1766 | 28.0 | 10528 | 0.3160 | 0.8715 | |
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| 0.1896 | 29.0 | 10904 | 0.3190 | 0.8715 | |
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| 0.157 | 30.0 | 11280 | 0.3195 | 0.8698 | |
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| 0.1522 | 31.0 | 11656 | 0.3183 | 0.8731 | |
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| 0.1888 | 32.0 | 12032 | 0.3211 | 0.8715 | |
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| 0.1615 | 33.0 | 12408 | 0.3233 | 0.8681 | |
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| 0.1503 | 34.0 | 12784 | 0.3209 | 0.8731 | |
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| 0.1481 | 35.0 | 13160 | 0.3244 | 0.8698 | |
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| 0.1788 | 36.0 | 13536 | 0.3242 | 0.8681 | |
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| 0.1497 | 37.0 | 13912 | 0.3239 | 0.8748 | |
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| 0.1343 | 38.0 | 14288 | 0.3226 | 0.8748 | |
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| 0.1659 | 39.0 | 14664 | 0.3268 | 0.8748 | |
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| 0.1781 | 40.0 | 15040 | 0.3250 | 0.8698 | |
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| 0.1644 | 41.0 | 15416 | 0.3283 | 0.8731 | |
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| 0.1354 | 42.0 | 15792 | 0.3269 | 0.8731 | |
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| 0.1533 | 43.0 | 16168 | 0.3272 | 0.8731 | |
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| 0.1541 | 44.0 | 16544 | 0.3272 | 0.8748 | |
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| 0.2043 | 45.0 | 16920 | 0.3294 | 0.8731 | |
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| 0.2146 | 46.0 | 17296 | 0.3299 | 0.8731 | |
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| 0.154 | 47.0 | 17672 | 0.3285 | 0.8715 | |
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| 0.1593 | 48.0 | 18048 | 0.3296 | 0.8731 | |
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| 0.1388 | 49.0 | 18424 | 0.3295 | 0.8731 | |
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| 0.1123 | 50.0 | 18800 | 0.3293 | 0.8715 | |
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### Framework versions |
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- Transformers 4.32.1 |
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- Pytorch 2.1.1+cu121 |
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- Datasets 2.12.0 |
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- Tokenizers 0.13.2 |
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