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5-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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+ - accuracy
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+ model-index:
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+ - name: 5-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: Accuracy
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+ type: accuracy
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+ value: 0.7643504531722054
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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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+ # 5-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: 0.7307
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+ - Accuracy: 0.7644
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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 | Accuracy |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | 2.0492 | 1.0 | 16 | 1.9604 | 0.3142 |
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+ | 1.8545 | 2.0 | 32 | 1.7361 | 0.4079 |
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+ | 1.724 | 3.0 | 48 | 1.5064 | 0.5166 |
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+ | 1.4761 | 4.0 | 64 | 1.3116 | 0.5710 |
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+ | 1.3215 | 5.0 | 80 | 1.2030 | 0.6344 |
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+ | 1.2325 | 6.0 | 96 | 1.0904 | 0.6254 |
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+ | 1.124 | 7.0 | 112 | 1.0145 | 0.6677 |
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+ | 1.0516 | 8.0 | 128 | 0.9864 | 0.6707 |
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+ | 0.9858 | 9.0 | 144 | 0.9372 | 0.6767 |
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+ | 0.9518 | 10.0 | 160 | 0.9161 | 0.6949 |
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+ | 0.9612 | 11.0 | 176 | 0.8916 | 0.6949 |
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+ | 0.8994 | 12.0 | 192 | 0.8579 | 0.7069 |
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+ | 0.8194 | 13.0 | 208 | 0.8281 | 0.7100 |
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+ | 0.8141 | 14.0 | 224 | 0.8064 | 0.7341 |
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+ | 0.8056 | 15.0 | 240 | 0.8272 | 0.7221 |
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+ | 0.7953 | 16.0 | 256 | 0.7751 | 0.7251 |
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+ | 0.7679 | 17.0 | 272 | 0.7638 | 0.7523 |
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+ | 0.7262 | 18.0 | 288 | 0.7867 | 0.7432 |
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+ | 0.7302 | 19.0 | 304 | 0.7835 | 0.7311 |
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+ | 0.7237 | 20.0 | 320 | 0.7698 | 0.7492 |
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+ | 0.6496 | 21.0 | 336 | 0.7618 | 0.7523 |
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+ | 0.6708 | 22.0 | 352 | 0.7595 | 0.7492 |
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+ | 0.6719 | 23.0 | 368 | 0.7455 | 0.7553 |
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+ | 0.6361 | 24.0 | 384 | 0.7993 | 0.7221 |
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+ | 0.6125 | 25.0 | 400 | 0.7372 | 0.7432 |
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+ | 0.6392 | 26.0 | 416 | 0.7321 | 0.7613 |
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+ | 0.6175 | 27.0 | 432 | 0.7310 | 0.7704 |
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+ | 0.5613 | 28.0 | 448 | 0.7244 | 0.7462 |
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+ | 0.5831 | 29.0 | 464 | 0.7535 | 0.7523 |
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+ | 0.5892 | 30.0 | 480 | 0.7299 | 0.7583 |
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+ | 0.5259 | 31.0 | 496 | 0.7211 | 0.7674 |
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+ | 0.5553 | 32.0 | 512 | 0.7564 | 0.7341 |
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+ | 0.5497 | 33.0 | 528 | 0.7233 | 0.7704 |
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+ | 0.5699 | 34.0 | 544 | 0.7314 | 0.7523 |
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+ | 0.5263 | 35.0 | 560 | 0.7334 | 0.7583 |
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+ | 0.4953 | 36.0 | 576 | 0.6991 | 0.7674 |
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+ | 0.5029 | 37.0 | 592 | 0.7191 | 0.7674 |
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+ | 0.5253 | 38.0 | 608 | 0.7233 | 0.7704 |
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+ | 0.4657 | 39.0 | 624 | 0.7204 | 0.7644 |
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+ | 0.498 | 40.0 | 640 | 0.7236 | 0.7674 |
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+ | 0.4768 | 41.0 | 656 | 0.7242 | 0.7734 |
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+ | 0.5016 | 42.0 | 672 | 0.7405 | 0.7553 |
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+ | 0.4774 | 43.0 | 688 | 0.7363 | 0.7674 |
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+ | 0.4859 | 44.0 | 704 | 0.7208 | 0.7734 |
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+ | 0.4628 | 45.0 | 720 | 0.7393 | 0.7674 |
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+ | 0.4515 | 46.0 | 736 | 0.7078 | 0.7734 |
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+ | 0.4297 | 47.0 | 752 | 0.7287 | 0.7674 |
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+ | 0.4023 | 48.0 | 768 | 0.7138 | 0.7734 |
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+ | 0.4404 | 49.0 | 784 | 0.7272 | 0.7674 |
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+ | 0.4236 | 50.0 | 800 | 0.7307 | 0.7644 |
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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