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smids_5x_deit_tiny_sgd_001_fold1

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  1. README.md +55 -55
  2. pytorch_model.bin +1 -1
README.md CHANGED
@@ -1,6 +1,6 @@
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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:
@@ -22,7 +22,7 @@ model-index:
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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
@@ -30,10 +30,10 @@ 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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@@ -65,56 +65,56 @@ The following hyperparameters were used during training:
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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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  ---
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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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  metrics:
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  - name: Accuracy
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  type: accuracy
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+ value: 0.8914858096828047
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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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  # smids_5x_deit_tiny_sgd_001_fold1
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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: 0.2974
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+ - Accuracy: 0.8915
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:-----:|:---------------:|:--------:|
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+ | 0.7214 | 1.0 | 376 | 0.7354 | 0.7112 |
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+ | 0.5305 | 2.0 | 752 | 0.5484 | 0.7780 |
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+ | 0.423 | 3.0 | 1128 | 0.4775 | 0.8063 |
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+ | 0.4098 | 4.0 | 1504 | 0.4302 | 0.8364 |
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+ | 0.4286 | 5.0 | 1880 | 0.4059 | 0.8497 |
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+ | 0.3605 | 6.0 | 2256 | 0.3872 | 0.8548 |
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+ | 0.3093 | 7.0 | 2632 | 0.3738 | 0.8648 |
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+ | 0.3348 | 8.0 | 3008 | 0.3632 | 0.8664 |
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+ | 0.3284 | 9.0 | 3384 | 0.3510 | 0.8765 |
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+ | 0.3008 | 10.0 | 3760 | 0.3447 | 0.8748 |
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+ | 0.289 | 11.0 | 4136 | 0.3398 | 0.8798 |
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+ | 0.2542 | 12.0 | 4512 | 0.3320 | 0.8848 |
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+ | 0.245 | 13.0 | 4888 | 0.3263 | 0.8865 |
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+ | 0.2258 | 14.0 | 5264 | 0.3225 | 0.8865 |
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+ | 0.3082 | 15.0 | 5640 | 0.3188 | 0.8848 |
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+ | 0.2685 | 16.0 | 6016 | 0.3171 | 0.8848 |
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+ | 0.2379 | 17.0 | 6392 | 0.3137 | 0.8865 |
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+ | 0.2778 | 18.0 | 6768 | 0.3111 | 0.8848 |
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+ | 0.2374 | 19.0 | 7144 | 0.3083 | 0.8848 |
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+ | 0.1845 | 20.0 | 7520 | 0.3061 | 0.8848 |
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+ | 0.2126 | 21.0 | 7896 | 0.3049 | 0.8865 |
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+ | 0.2068 | 22.0 | 8272 | 0.3078 | 0.8831 |
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+ | 0.2364 | 23.0 | 8648 | 0.3060 | 0.8798 |
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+ | 0.1851 | 24.0 | 9024 | 0.3035 | 0.8881 |
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+ | 0.2035 | 25.0 | 9400 | 0.3013 | 0.8848 |
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+ | 0.2146 | 26.0 | 9776 | 0.3016 | 0.8881 |
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+ | 0.1495 | 27.0 | 10152 | 0.2986 | 0.8915 |
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+ | 0.1962 | 28.0 | 10528 | 0.2989 | 0.8898 |
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+ | 0.2019 | 29.0 | 10904 | 0.2993 | 0.8881 |
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+ | 0.1531 | 30.0 | 11280 | 0.2975 | 0.8932 |
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+ | 0.1643 | 31.0 | 11656 | 0.2990 | 0.8898 |
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+ | 0.2082 | 32.0 | 12032 | 0.2991 | 0.8881 |
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+ | 0.1845 | 33.0 | 12408 | 0.2980 | 0.8915 |
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+ | 0.1333 | 34.0 | 12784 | 0.2976 | 0.8932 |
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+ | 0.1524 | 35.0 | 13160 | 0.3000 | 0.8865 |
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+ | 0.1908 | 36.0 | 13536 | 0.2977 | 0.8915 |
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+ | 0.1391 | 37.0 | 13912 | 0.2964 | 0.8948 |
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+ | 0.1756 | 38.0 | 14288 | 0.2975 | 0.8915 |
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+ | 0.2131 | 39.0 | 14664 | 0.2969 | 0.8932 |
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+ | 0.1588 | 40.0 | 15040 | 0.2977 | 0.8898 |
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+ | 0.1631 | 41.0 | 15416 | 0.2962 | 0.8932 |
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+ | 0.1431 | 42.0 | 15792 | 0.2974 | 0.8915 |
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+ | 0.1556 | 43.0 | 16168 | 0.2976 | 0.8898 |
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+ | 0.1705 | 44.0 | 16544 | 0.2978 | 0.8915 |
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+ | 0.1792 | 45.0 | 16920 | 0.2986 | 0.8898 |
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+ | 0.1949 | 46.0 | 17296 | 0.2975 | 0.8915 |
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+ | 0.1472 | 47.0 | 17672 | 0.2972 | 0.8915 |
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+ | 0.139 | 48.0 | 18048 | 0.2974 | 0.8915 |
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+ | 0.1452 | 49.0 | 18424 | 0.2974 | 0.8915 |
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+ | 0.1388 | 50.0 | 18800 | 0.2974 | 0.8915 |
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  ### Framework versions
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