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10-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: 10-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: 0.9061888902800384
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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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+ # 10-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: 0.2197
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+ - F1: 0.9062
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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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+ | 0.7175 | 1.0 | 18 | 0.6978 | 0.5508 |
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+ | 0.6996 | 2.0 | 36 | 0.6699 | 0.7605 |
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+ | 0.659 | 3.0 | 54 | 0.6291 | 0.8044 |
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+ | 0.5937 | 4.0 | 72 | 0.5778 | 0.7920 |
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+ | 0.5124 | 5.0 | 90 | 0.5113 | 0.7934 |
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+ | 0.4668 | 6.0 | 108 | 0.4066 | 0.7934 |
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+ | 0.4079 | 7.0 | 126 | 0.4105 | 0.7934 |
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+ | 0.363 | 8.0 | 144 | 0.3652 | 0.7934 |
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+ | 0.337 | 9.0 | 162 | 0.3410 | 0.7934 |
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+ | 0.3172 | 10.0 | 180 | 0.3272 | 0.7934 |
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+ | 0.3082 | 11.0 | 198 | 0.2930 | 0.7934 |
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+ | 0.2967 | 12.0 | 216 | 0.2814 | 0.7934 |
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+ | 0.2889 | 13.0 | 234 | 0.2665 | 0.7934 |
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+ | 0.2636 | 14.0 | 252 | 0.2846 | 0.7934 |
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+ | 0.2694 | 15.0 | 270 | 0.2610 | 0.7934 |
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+ | 0.2663 | 16.0 | 288 | 0.2828 | 0.7934 |
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+ | 0.2573 | 17.0 | 306 | 0.2615 | 0.7934 |
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+ | 0.2558 | 18.0 | 324 | 0.2606 | 0.7934 |
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+ | 0.2492 | 19.0 | 342 | 0.2532 | 0.7934 |
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+ | 0.2513 | 20.0 | 360 | 0.2559 | 0.7934 |
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+ | 0.2429 | 21.0 | 378 | 0.2497 | 0.7934 |
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+ | 0.2361 | 22.0 | 396 | 0.2412 | 0.7934 |
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+ | 0.2423 | 23.0 | 414 | 0.2494 | 0.8235 |
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+ | 0.2479 | 24.0 | 432 | 0.2446 | 0.8290 |
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+ | 0.2237 | 25.0 | 450 | 0.2425 | 0.8428 |
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+ | 0.2282 | 26.0 | 468 | 0.2446 | 0.8573 |
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+ | 0.2343 | 27.0 | 486 | 0.2348 | 0.8344 |
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+ | 0.2169 | 28.0 | 504 | 0.2358 | 0.8547 |
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+ | 0.2169 | 29.0 | 522 | 0.2400 | 0.8622 |
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+ | 0.2341 | 30.0 | 540 | 0.2342 | 0.8579 |
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+ | 0.2241 | 31.0 | 558 | 0.2266 | 0.8511 |
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+ | 0.2132 | 32.0 | 576 | 0.2250 | 0.8662 |
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+ | 0.2155 | 33.0 | 594 | 0.2222 | 0.8485 |
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+ | 0.2014 | 34.0 | 612 | 0.2279 | 0.8659 |
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+ | 0.2033 | 35.0 | 630 | 0.2296 | 0.8886 |
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+ | 0.1993 | 36.0 | 648 | 0.2252 | 0.8909 |
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+ | 0.228 | 37.0 | 666 | 0.2226 | 0.8742 |
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+ | 0.2292 | 38.0 | 684 | 0.2274 | 0.9030 |
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+ | 0.202 | 39.0 | 702 | 0.2307 | 0.8997 |
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+ | 0.2133 | 40.0 | 720 | 0.2244 | 0.8977 |
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+ | 0.214 | 41.0 | 738 | 0.2281 | 0.9053 |
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+ | 0.2203 | 42.0 | 756 | 0.2251 | 0.9020 |
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+ | 0.2071 | 43.0 | 774 | 0.2214 | 0.8848 |
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+ | 0.2125 | 44.0 | 792 | 0.2196 | 0.8932 |
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+ | 0.2137 | 45.0 | 810 | 0.2187 | 0.8811 |
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+ | 0.2073 | 46.0 | 828 | 0.2183 | 0.9020 |
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+ | 0.2119 | 47.0 | 846 | 0.2185 | 0.9109 |
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+ | 0.2018 | 48.0 | 864 | 0.2199 | 0.8943 |
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+ | 0.1971 | 49.0 | 882 | 0.2211 | 0.9053 |
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+ | 0.2079 | 50.0 | 900 | 0.2197 | 0.9062 |
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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