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7-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: 7-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: 0.7449020840597932
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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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+ # 7-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: 0.7844
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+ - F1: 0.7449
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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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+ | 2.0948 | 1.0 | 18 | 1.9801 | 0.1856 |
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+ | 1.916 | 2.0 | 36 | 1.7571 | 0.3242 |
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+ | 1.6873 | 3.0 | 54 | 1.5333 | 0.4149 |
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+ | 1.4576 | 4.0 | 72 | 1.3515 | 0.4656 |
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+ | 1.2824 | 5.0 | 90 | 1.2288 | 0.4936 |
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+ | 1.2004 | 6.0 | 108 | 1.1050 | 0.5462 |
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+ | 1.1264 | 7.0 | 126 | 1.0643 | 0.5713 |
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+ | 1.0149 | 8.0 | 144 | 1.0612 | 0.5718 |
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+ | 0.9839 | 9.0 | 162 | 0.9897 | 0.6266 |
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+ | 0.9001 | 10.0 | 180 | 0.9542 | 0.6710 |
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+ | 0.9093 | 11.0 | 198 | 0.8993 | 0.6811 |
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+ | 0.8824 | 12.0 | 216 | 0.8877 | 0.7018 |
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+ | 0.8237 | 13.0 | 234 | 0.8970 | 0.7071 |
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+ | 0.8446 | 14.0 | 252 | 0.8619 | 0.7084 |
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+ | 0.7766 | 15.0 | 270 | 0.8271 | 0.7331 |
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+ | 0.7405 | 16.0 | 288 | 0.8516 | 0.7237 |
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+ | 0.7672 | 17.0 | 306 | 0.8036 | 0.7223 |
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+ | 0.7149 | 18.0 | 324 | 0.8188 | 0.7186 |
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+ | 0.7 | 19.0 | 342 | 0.8391 | 0.7274 |
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+ | 0.7011 | 20.0 | 360 | 0.7922 | 0.7424 |
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+ | 0.695 | 21.0 | 378 | 0.8065 | 0.7394 |
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+ | 0.6655 | 22.0 | 396 | 0.7783 | 0.7473 |
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+ | 0.6377 | 23.0 | 414 | 0.7977 | 0.7296 |
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+ | 0.6884 | 24.0 | 432 | 0.7724 | 0.7387 |
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+ | 0.614 | 25.0 | 450 | 0.8372 | 0.7351 |
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+ | 0.6008 | 26.0 | 468 | 0.8229 | 0.7277 |
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+ | 0.6402 | 27.0 | 486 | 0.7958 | 0.7300 |
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+ | 0.592 | 28.0 | 504 | 0.8222 | 0.7264 |
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+ | 0.5774 | 29.0 | 522 | 0.7613 | 0.7511 |
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+ | 0.584 | 30.0 | 540 | 0.7866 | 0.7377 |
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+ | 0.558 | 31.0 | 558 | 0.8298 | 0.7351 |
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+ | 0.5871 | 32.0 | 576 | 0.7727 | 0.7494 |
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+ | 0.5608 | 33.0 | 594 | 0.7753 | 0.7695 |
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+ | 0.5385 | 34.0 | 612 | 0.7585 | 0.7575 |
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+ | 0.5461 | 35.0 | 630 | 0.7664 | 0.7521 |
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+ | 0.506 | 36.0 | 648 | 0.7624 | 0.7581 |
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+ | 0.5132 | 37.0 | 666 | 0.7914 | 0.7347 |
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+ | 0.5083 | 38.0 | 684 | 0.7913 | 0.7425 |
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+ | 0.5042 | 39.0 | 702 | 0.7704 | 0.7556 |
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+ | 0.4539 | 40.0 | 720 | 0.7590 | 0.7578 |
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+ | 0.4714 | 41.0 | 738 | 0.7912 | 0.7503 |
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+ | 0.4681 | 42.0 | 756 | 0.7838 | 0.7420 |
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+ | 0.4482 | 43.0 | 774 | 0.7781 | 0.7345 |
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+ | 0.4535 | 44.0 | 792 | 0.7823 | 0.7415 |
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+ | 0.4284 | 45.0 | 810 | 0.8104 | 0.7449 |
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+ | 0.436 | 46.0 | 828 | 0.7829 | 0.7421 |
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+ | 0.4526 | 47.0 | 846 | 0.7932 | 0.7567 |
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+ | 0.4672 | 48.0 | 864 | 0.7827 | 0.7411 |
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+ | 0.4171 | 49.0 | 882 | 0.7835 | 0.7447 |
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+ | 0.4126 | 50.0 | 900 | 0.7844 | 0.7449 |
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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