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Oppoizer
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Output-prova_melanoma

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update model card README.md

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@@ -21,7 +21,7 @@ model-index:
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  metrics:
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  - name: Accuracy
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  type: accuracy
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- value: 0.94
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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
@@ -31,8 +31,8 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [UnipaPolitoUnimore/vit-large-patch32-384-melanoma](https://huggingface.co/UnipaPolitoUnimore/vit-large-patch32-384-melanoma) on the imagefolder dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.2030
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- - Accuracy: 0.94
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  ## Model description
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@@ -51,7 +51,7 @@ More information needed
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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- - learning_rate: 1e-05
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  - train_batch_size: 16
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  - eval_batch_size: 16
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  - seed: 42
@@ -66,46 +66,46 @@ 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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- | 0.5144 | 1.0 | 47 | 0.2077 | 0.9667 |
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- | 0.6803 | 2.0 | 94 | 0.1974 | 0.9733 |
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- | 0.6678 | 3.0 | 141 | 0.1827 | 0.9733 |
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- | 0.081 | 4.0 | 188 | 0.1547 | 0.9667 |
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- | 0.2983 | 5.0 | 235 | 0.1488 | 0.96 |
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- | 0.4184 | 6.0 | 282 | 0.1981 | 0.9533 |
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- | 0.1672 | 7.0 | 329 | 0.1975 | 0.9533 |
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- | 0.0593 | 8.0 | 376 | 0.1936 | 0.9533 |
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- | 0.1465 | 9.0 | 423 | 0.2012 | 0.96 |
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- | 0.1286 | 10.0 | 470 | 0.1893 | 0.9467 |
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- | 0.2288 | 11.0 | 517 | 0.2153 | 0.9533 |
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- | 0.0711 | 12.0 | 564 | 0.2097 | 0.9467 |
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- | 0.0688 | 13.0 | 611 | 0.2534 | 0.9467 |
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- | 0.1424 | 14.0 | 658 | 0.2244 | 0.94 |
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- | 0.0376 | 15.0 | 705 | 0.1793 | 0.96 |
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- | 0.1185 | 16.0 | 752 | 0.1551 | 0.9667 |
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- | 0.103 | 17.0 | 799 | 0.2280 | 0.94 |
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- | 0.2761 | 18.0 | 846 | 0.1801 | 0.96 |
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- | 0.331 | 19.0 | 893 | 0.1819 | 0.96 |
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- | 0.1042 | 20.0 | 940 | 0.1995 | 0.96 |
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- | 0.218 | 21.0 | 987 | 0.2048 | 0.96 |
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- | 0.1605 | 22.0 | 1034 | 0.2818 | 0.94 |
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- | 0.1551 | 23.0 | 1081 | 0.2406 | 0.9467 |
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- | 0.1109 | 24.0 | 1128 | 0.1850 | 0.96 |
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- | 0.2726 | 25.0 | 1175 | 0.2096 | 0.9467 |
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- | 0.1511 | 26.0 | 1222 | 0.2317 | 0.9467 |
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- | 0.2063 | 27.0 | 1269 | 0.2069 | 0.9533 |
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- | 0.1137 | 28.0 | 1316 | 0.2275 | 0.9267 |
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- | 0.1694 | 29.0 | 1363 | 0.2036 | 0.9533 |
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- | 0.0561 | 30.0 | 1410 | 0.2125 | 0.9467 |
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- | 0.076 | 31.0 | 1457 | 0.2198 | 0.94 |
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- | 0.0575 | 32.0 | 1504 | 0.1990 | 0.9533 |
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- | 0.1484 | 33.0 | 1551 | 0.1840 | 0.9533 |
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- | 0.127 | 34.0 | 1598 | 0.2080 | 0.9467 |
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- | 0.1309 | 35.0 | 1645 | 0.2118 | 0.94 |
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- | 0.0675 | 36.0 | 1692 | 0.2273 | 0.94 |
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- | 0.0809 | 37.0 | 1739 | 0.2099 | 0.94 |
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- | 0.1067 | 38.0 | 1786 | 0.1905 | 0.96 |
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- | 0.0636 | 39.0 | 1833 | 0.1979 | 0.9467 |
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- | 0.0764 | 40.0 | 1880 | 0.2030 | 0.94 |
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  ### Framework versions
 
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  metrics:
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  - name: Accuracy
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  type: accuracy
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+ value: 0.9466666666666667
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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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  This model is a fine-tuned version of [UnipaPolitoUnimore/vit-large-patch32-384-melanoma](https://huggingface.co/UnipaPolitoUnimore/vit-large-patch32-384-melanoma) on the imagefolder dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.2202
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+ - Accuracy: 0.9467
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  ## Model description
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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+ - learning_rate: 1.5e-05
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  - train_batch_size: 16
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  - eval_batch_size: 16
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  - seed: 42
 
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | 0.4501 | 1.0 | 47 | 0.2094 | 0.9667 |
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+ | 0.5554 | 2.0 | 94 | 0.2010 | 0.9733 |
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+ | 0.5299 | 3.0 | 141 | 0.1595 | 0.9733 |
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+ | 0.0854 | 4.0 | 188 | 0.1529 | 0.9667 |
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+ | 0.2766 | 5.0 | 235 | 0.1466 | 0.9667 |
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+ | 0.3158 | 6.0 | 282 | 0.1916 | 0.96 |
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+ | 0.1322 | 7.0 | 329 | 0.1924 | 0.9733 |
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+ | 0.065 | 8.0 | 376 | 0.1905 | 0.9533 |
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+ | 0.1565 | 9.0 | 423 | 0.2025 | 0.9467 |
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+ | 0.1296 | 10.0 | 470 | 0.2367 | 0.9333 |
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+ | 0.2448 | 11.0 | 517 | 0.2255 | 0.94 |
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+ | 0.067 | 12.0 | 564 | 0.2315 | 0.94 |
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+ | 0.0764 | 13.0 | 611 | 0.2479 | 0.9467 |
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+ | 0.1472 | 14.0 | 658 | 0.2599 | 0.9333 |
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+ | 0.0483 | 15.0 | 705 | 0.1911 | 0.9533 |
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+ | 0.0961 | 16.0 | 752 | 0.1869 | 0.9533 |
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+ | 0.1146 | 17.0 | 799 | 0.2355 | 0.9333 |
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+ | 0.2117 | 18.0 | 846 | 0.1930 | 0.94 |
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+ | 0.2859 | 19.0 | 893 | 0.1902 | 0.9467 |
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+ | 0.0798 | 20.0 | 940 | 0.2436 | 0.9333 |
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+ | 0.16 | 21.0 | 987 | 0.2341 | 0.94 |
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+ | 0.1968 | 22.0 | 1034 | 0.3552 | 0.9067 |
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+ | 0.1049 | 23.0 | 1081 | 0.2541 | 0.9267 |
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+ | 0.1102 | 24.0 | 1128 | 0.1839 | 0.9467 |
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+ | 0.3039 | 25.0 | 1175 | 0.2269 | 0.9333 |
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+ | 0.1188 | 26.0 | 1222 | 0.2063 | 0.9533 |
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+ | 0.2008 | 27.0 | 1269 | 0.1972 | 0.94 |
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+ | 0.1113 | 28.0 | 1316 | 0.2157 | 0.94 |
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+ | 0.1377 | 29.0 | 1363 | 0.2031 | 0.9533 |
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+ | 0.042 | 30.0 | 1410 | 0.2124 | 0.9533 |
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+ | 0.0841 | 31.0 | 1457 | 0.2174 | 0.94 |
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+ | 0.046 | 32.0 | 1504 | 0.2136 | 0.9467 |
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+ | 0.1309 | 33.0 | 1551 | 0.1981 | 0.96 |
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+ | 0.1207 | 34.0 | 1598 | 0.2334 | 0.94 |
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+ | 0.1216 | 35.0 | 1645 | 0.2238 | 0.94 |
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+ | 0.0518 | 36.0 | 1692 | 0.2441 | 0.9467 |
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+ | 0.0852 | 37.0 | 1739 | 0.2243 | 0.9467 |
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+ | 0.0853 | 38.0 | 1786 | 0.2028 | 0.9533 |
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+ | 0.055 | 39.0 | 1833 | 0.2124 | 0.9467 |
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+ | 0.0646 | 40.0 | 1880 | 0.2202 | 0.9467 |
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  ### Framework versions