| | --- |
| | license: apache-2.0 |
| | tags: |
| | - generated_from_trainer |
| | datasets: |
| | - imagefolder |
| | metrics: |
| | - accuracy |
| | model-index: |
| | - name: Output-prova_melanoma |
| | results: |
| | - task: |
| | name: Image Classification |
| | type: image-classification |
| | dataset: |
| | name: imagefolder |
| | type: imagefolder |
| | config: default |
| | split: train |
| | args: default |
| | metrics: |
| | - name: Accuracy |
| | type: accuracy |
| | value: 0.9466666666666667 |
| | --- |
| | |
| | <!-- This model card has been generated automatically according to the information the Trainer had access to. You |
| | should probably proofread and complete it, then remove this comment. --> |
| |
|
| | # Output-prova_melanoma |
| | |
| | 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. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.2202 |
| | - Accuracy: 0.9467 |
| | |
| | ## Model description |
| | |
| | More information needed |
| | |
| | ## Intended uses & limitations |
| | |
| | More information needed |
| | |
| | ## Training and evaluation data |
| | |
| | More information needed |
| | |
| | ## Training procedure |
| | |
| | ### Training hyperparameters |
| | |
| | The following hyperparameters were used during training: |
| | - learning_rate: 1.5e-05 |
| | - train_batch_size: 16 |
| | - eval_batch_size: 16 |
| | - seed: 42 |
| | - gradient_accumulation_steps: 4 |
| | - total_train_batch_size: 64 |
| | - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| | - lr_scheduler_type: linear |
| | - lr_scheduler_warmup_ratio: 0.1 |
| | - num_epochs: 40 |
| | |
| | ### Training results |
| | |
| | | Training Loss | Epoch | Step | Validation Loss | Accuracy | |
| | |:-------------:|:-----:|:----:|:---------------:|:--------:| |
| | | 0.4501 | 1.0 | 47 | 0.2094 | 0.9667 | |
| | | 0.5554 | 2.0 | 94 | 0.2010 | 0.9733 | |
| | | 0.5299 | 3.0 | 141 | 0.1595 | 0.9733 | |
| | | 0.0854 | 4.0 | 188 | 0.1529 | 0.9667 | |
| | | 0.2766 | 5.0 | 235 | 0.1466 | 0.9667 | |
| | | 0.3158 | 6.0 | 282 | 0.1916 | 0.96 | |
| | | 0.1322 | 7.0 | 329 | 0.1924 | 0.9733 | |
| | | 0.065 | 8.0 | 376 | 0.1905 | 0.9533 | |
| | | 0.1565 | 9.0 | 423 | 0.2025 | 0.9467 | |
| | | 0.1296 | 10.0 | 470 | 0.2367 | 0.9333 | |
| | | 0.2448 | 11.0 | 517 | 0.2255 | 0.94 | |
| | | 0.067 | 12.0 | 564 | 0.2315 | 0.94 | |
| | | 0.0764 | 13.0 | 611 | 0.2479 | 0.9467 | |
| | | 0.1472 | 14.0 | 658 | 0.2599 | 0.9333 | |
| | | 0.0483 | 15.0 | 705 | 0.1911 | 0.9533 | |
| | | 0.0961 | 16.0 | 752 | 0.1869 | 0.9533 | |
| | | 0.1146 | 17.0 | 799 | 0.2355 | 0.9333 | |
| | | 0.2117 | 18.0 | 846 | 0.1930 | 0.94 | |
| | | 0.2859 | 19.0 | 893 | 0.1902 | 0.9467 | |
| | | 0.0798 | 20.0 | 940 | 0.2436 | 0.9333 | |
| | | 0.16 | 21.0 | 987 | 0.2341 | 0.94 | |
| | | 0.1968 | 22.0 | 1034 | 0.3552 | 0.9067 | |
| | | 0.1049 | 23.0 | 1081 | 0.2541 | 0.9267 | |
| | | 0.1102 | 24.0 | 1128 | 0.1839 | 0.9467 | |
| | | 0.3039 | 25.0 | 1175 | 0.2269 | 0.9333 | |
| | | 0.1188 | 26.0 | 1222 | 0.2063 | 0.9533 | |
| | | 0.2008 | 27.0 | 1269 | 0.1972 | 0.94 | |
| | | 0.1113 | 28.0 | 1316 | 0.2157 | 0.94 | |
| | | 0.1377 | 29.0 | 1363 | 0.2031 | 0.9533 | |
| | | 0.042 | 30.0 | 1410 | 0.2124 | 0.9533 | |
| | | 0.0841 | 31.0 | 1457 | 0.2174 | 0.94 | |
| | | 0.046 | 32.0 | 1504 | 0.2136 | 0.9467 | |
| | | 0.1309 | 33.0 | 1551 | 0.1981 | 0.96 | |
| | | 0.1207 | 34.0 | 1598 | 0.2334 | 0.94 | |
| | | 0.1216 | 35.0 | 1645 | 0.2238 | 0.94 | |
| | | 0.0518 | 36.0 | 1692 | 0.2441 | 0.9467 | |
| | | 0.0852 | 37.0 | 1739 | 0.2243 | 0.9467 | |
| | | 0.0853 | 38.0 | 1786 | 0.2028 | 0.9533 | |
| | | 0.055 | 39.0 | 1833 | 0.2124 | 0.9467 | |
| | | 0.0646 | 40.0 | 1880 | 0.2202 | 0.9467 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.30.0.dev0 |
| | - Pytorch 1.13.1+cu116 |
| | - Datasets 2.11.0 |
| | - Tokenizers 0.13.3 |
| | |
