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4-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: 4-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: 0.7123519458544839
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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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+ # 4-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: 0.9186
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+ - Accuracy: 0.7124
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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: 20
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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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+ | 2.0441 | 1.0 | 14 | 1.9084 | 0.3164 |
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+ | 1.8716 | 2.0 | 28 | 1.6532 | 0.4484 |
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+ | 1.4727 | 3.0 | 42 | 1.4218 | 0.5228 |
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+ | 1.3452 | 4.0 | 56 | 1.3037 | 0.5736 |
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+ | 1.2518 | 5.0 | 70 | 1.2799 | 0.5584 |
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+ | 1.1646 | 6.0 | 84 | 1.1892 | 0.6244 |
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+ | 1.1358 | 7.0 | 98 | 1.1543 | 0.6074 |
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+ | 1.0664 | 8.0 | 112 | 1.1060 | 0.6277 |
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+ | 1.041 | 9.0 | 126 | 1.0434 | 0.6667 |
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+ | 1.002 | 10.0 | 140 | 1.0337 | 0.6582 |
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+ | 0.9867 | 11.0 | 154 | 1.0373 | 0.6582 |
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+ | 0.9485 | 12.0 | 168 | 0.9866 | 0.6887 |
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+ | 0.9121 | 13.0 | 182 | 0.9827 | 0.6785 |
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+ | 0.918 | 14.0 | 196 | 0.9588 | 0.7039 |
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+ | 0.8882 | 15.0 | 210 | 0.9576 | 0.7005 |
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+ | 0.873 | 16.0 | 224 | 0.9450 | 0.7022 |
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+ | 0.8469 | 17.0 | 238 | 0.9266 | 0.7090 |
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+ | 0.814 | 18.0 | 252 | 0.9463 | 0.6971 |
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+ | 0.8206 | 19.0 | 266 | 0.9201 | 0.7090 |
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+ | 0.8078 | 20.0 | 280 | 0.9186 | 0.7124 |
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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