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11-classifier-finetuned-padchest

Image Classification
Transformers
PyTorch
resnet
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: 11-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: 0.5097608873456089
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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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+ # 11-classifier-finetuned-padchest
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+
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+ This model is a fine-tuned version of [microsoft/resnet-50](https://huggingface.co/microsoft/resnet-50) on the imagefolder dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 1.1743
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+ - F1: 0.5098
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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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+ | 2.0747 | 1.0 | 18 | 2.0666 | 0.1549 |
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+ | 2.0661 | 2.0 | 36 | 2.0560 | 0.1777 |
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+ | 2.0497 | 3.0 | 54 | 2.0385 | 0.2169 |
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+ | 2.018 | 4.0 | 72 | 2.0047 | 0.2515 |
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+ | 1.9792 | 5.0 | 90 | 1.9773 | 0.2329 |
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+ | 1.9619 | 6.0 | 108 | 1.9421 | 0.2321 |
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+ | 1.9186 | 7.0 | 126 | 1.9145 | 0.2055 |
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+ | 1.8838 | 8.0 | 144 | 1.8976 | 0.2596 |
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+ | 1.8402 | 9.0 | 162 | 1.8444 | 0.2337 |
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+ | 1.7906 | 10.0 | 180 | 1.7951 | 0.2397 |
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+ | 1.7716 | 11.0 | 198 | 1.7695 | 0.3373 |
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+ | 1.7474 | 12.0 | 216 | 1.7940 | 0.3209 |
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+ | 1.6957 | 13.0 | 234 | 1.7425 | 0.3314 |
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+ | 1.6791 | 14.0 | 252 | 1.6727 | 0.3558 |
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+ | 1.6483 | 15.0 | 270 | 1.6638 | 0.3895 |
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+ | 1.614 | 16.0 | 288 | 1.6513 | 0.4186 |
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+ | 1.6166 | 17.0 | 306 | 1.6002 | 0.4406 |
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+ | 1.5654 | 18.0 | 324 | 1.5528 | 0.4627 |
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+ | 1.5145 | 19.0 | 342 | 1.5571 | 0.4676 |
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+ | 1.5049 | 20.0 | 360 | 1.4334 | 0.4364 |
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+ | 1.457 | 21.0 | 378 | 1.4711 | 0.4535 |
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+ | 1.4516 | 22.0 | 396 | 1.5013 | 0.4516 |
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+ | 1.4172 | 23.0 | 414 | 1.3614 | 0.4682 |
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+ | 1.3817 | 24.0 | 432 | 1.3519 | 0.4545 |
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+ | 1.3987 | 25.0 | 450 | 1.3806 | 0.4759 |
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+ | 1.4063 | 26.0 | 468 | 1.2961 | 0.4866 |
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+ | 1.3684 | 27.0 | 486 | 1.3328 | 0.4768 |
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+ | 1.3789 | 28.0 | 504 | 1.2810 | 0.4859 |
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+ | 1.341 | 29.0 | 522 | 1.3227 | 0.4737 |
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+ | 1.3574 | 30.0 | 540 | 1.2406 | 0.5025 |
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+ | 1.357 | 31.0 | 558 | 1.2427 | 0.5033 |
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+ | 1.3204 | 32.0 | 576 | 1.2478 | 0.5053 |
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+ | 1.3122 | 33.0 | 594 | 1.2205 | 0.5133 |
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+ | 1.334 | 34.0 | 612 | 1.2138 | 0.5204 |
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+ | 1.2998 | 35.0 | 630 | 1.2122 | 0.5111 |
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+ | 1.3097 | 36.0 | 648 | 1.2118 | 0.5102 |
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+ | 1.2956 | 37.0 | 666 | 1.2077 | 0.5163 |
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+ | 1.3058 | 38.0 | 684 | 1.2023 | 0.5157 |
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+ | 1.2851 | 39.0 | 702 | 1.1968 | 0.5067 |
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+ | 1.2728 | 40.0 | 720 | 1.1940 | 0.5169 |
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+ | 1.2653 | 41.0 | 738 | 1.1700 | 0.5165 |
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+ | 1.2837 | 42.0 | 756 | 1.1767 | 0.5262 |
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+ | 1.2789 | 43.0 | 774 | 1.1885 | 0.5146 |
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+ | 1.2343 | 44.0 | 792 | 1.1925 | 0.5101 |
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+ | 1.2454 | 45.0 | 810 | 1.1874 | 0.5119 |
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+ | 1.2922 | 46.0 | 828 | 1.1845 | 0.5216 |
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+ | 1.2547 | 47.0 | 846 | 1.1920 | 0.5299 |
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+ | 1.272 | 48.0 | 864 | 1.1732 | 0.5225 |
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+ | 1.2506 | 49.0 | 882 | 1.1722 | 0.5117 |
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+ | 1.2494 | 50.0 | 900 | 1.1743 | 0.5098 |
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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