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9-classifier-finetuned-padchest

Image Classification
Transformers
PyTorch
vit
Generated from Trainer
Eval Results
Inference Endpoints
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+ ---
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+ license: apache-2.0
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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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+ - f1
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+ model-index:
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+ - name: 9-classifier-finetuned-padchest
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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: train
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+ args: default
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+ metrics:
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+ - name: F1
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+ type: f1
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+ value: 0.9562502564102563
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+ ---
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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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+
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+ # 9-classifier-finetuned-padchest
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+
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+ This model is a fine-tuned version of [nickmuchi/vit-finetuned-chest-xray-pneumonia](https://huggingface.co/nickmuchi/vit-finetuned-chest-xray-pneumonia) on the imagefolder dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.1585
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+ - F1: 0.9563
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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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: 32
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+ - eval_batch_size: 32
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+ - seed: 42
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+ - gradient_accumulation_steps: 4
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+ - total_train_batch_size: 128
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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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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | F1 |
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+ |:-------------:|:-----:|:----:|:---------------:|:------:|
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+ | 2.5332 | 1.0 | 18 | 0.5695 | 0.7920 |
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+ | 0.4488 | 2.0 | 36 | 0.3419 | 0.7934 |
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+ | 0.3259 | 3.0 | 54 | 0.2451 | 0.7934 |
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+ | 0.2795 | 4.0 | 72 | 0.1954 | 0.9443 |
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+ | 0.2348 | 5.0 | 90 | 0.1698 | 0.9343 |
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+ | 0.1937 | 6.0 | 108 | 0.1829 | 0.9297 |
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+ | 0.1851 | 7.0 | 126 | 0.1484 | 0.9454 |
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+ | 0.1925 | 8.0 | 144 | 0.1330 | 0.9545 |
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+ | 0.1614 | 9.0 | 162 | 0.1403 | 0.9387 |
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+ | 0.1734 | 10.0 | 180 | 0.1221 | 0.9531 |
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+ | 0.1697 | 11.0 | 198 | 0.1142 | 0.9524 |
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+ | 0.1824 | 12.0 | 216 | 0.1129 | 0.9586 |
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+ | 0.1336 | 13.0 | 234 | 0.1369 | 0.9441 |
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+ | 0.1596 | 14.0 | 252 | 0.1181 | 0.9540 |
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+ | 0.1474 | 15.0 | 270 | 0.1116 | 0.9646 |
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+ | 0.1256 | 16.0 | 288 | 0.1035 | 0.9598 |
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+ | 0.1398 | 17.0 | 306 | 0.1195 | 0.9519 |
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+ | 0.1219 | 18.0 | 324 | 0.1123 | 0.9588 |
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+ | 0.1114 | 19.0 | 342 | 0.1126 | 0.9586 |
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+ | 0.1089 | 20.0 | 360 | 0.1083 | 0.9584 |
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+ | 0.1123 | 21.0 | 378 | 0.1038 | 0.9554 |
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+ | 0.1241 | 22.0 | 396 | 0.0927 | 0.9657 |
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+ | 0.099 | 23.0 | 414 | 0.1397 | 0.9559 |
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+ | 0.1025 | 24.0 | 432 | 0.1201 | 0.9584 |
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+ | 0.1088 | 25.0 | 450 | 0.0894 | 0.9627 |
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+ | 0.0953 | 26.0 | 468 | 0.1083 | 0.9632 |
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+ | 0.0953 | 27.0 | 486 | 0.1061 | 0.9592 |
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+ | 0.0831 | 28.0 | 504 | 0.1129 | 0.9570 |
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+ | 0.0836 | 29.0 | 522 | 0.1123 | 0.9598 |
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+ | 0.0705 | 30.0 | 540 | 0.1611 | 0.9499 |
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+ | 0.1047 | 31.0 | 558 | 0.1191 | 0.9570 |
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+ | 0.0803 | 32.0 | 576 | 0.1440 | 0.9563 |
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+ | 0.0852 | 33.0 | 594 | 0.1149 | 0.9541 |
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+ | 0.0588 | 34.0 | 612 | 0.1830 | 0.9489 |
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+ | 0.0701 | 35.0 | 630 | 0.1475 | 0.9592 |
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+ | 0.0607 | 36.0 | 648 | 0.1350 | 0.9627 |
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+ | 0.0749 | 37.0 | 666 | 0.1389 | 0.9563 |
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+ | 0.073 | 38.0 | 684 | 0.1463 | 0.9559 |
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+ | 0.0579 | 39.0 | 702 | 0.1289 | 0.9595 |
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+ | 0.0757 | 40.0 | 720 | 0.1585 | 0.9584 |
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+ | 0.0538 | 41.0 | 738 | 0.1565 | 0.9588 |
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+ | 0.0461 | 42.0 | 756 | 0.1630 | 0.9559 |
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+ | 0.072 | 43.0 | 774 | 0.1704 | 0.9554 |
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+ | 0.0517 | 44.0 | 792 | 0.1657 | 0.9559 |
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+ | 0.0524 | 45.0 | 810 | 0.1358 | 0.9570 |
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+ | 0.0569 | 46.0 | 828 | 0.1538 | 0.9533 |
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+ | 0.0506 | 47.0 | 846 | 0.1579 | 0.9588 |
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+ | 0.0506 | 48.0 | 864 | 0.1505 | 0.9566 |
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+ | 0.0538 | 49.0 | 882 | 0.1593 | 0.9588 |
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+ | 0.0532 | 50.0 | 900 | 0.1585 | 0.9563 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.28.0.dev0
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+ - Pytorch 2.0.0+cu117
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+ - Datasets 2.18.0
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+ - Tokenizers 0.13.3