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README.md ADDED
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+ ---
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+ license: apache-2.0
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+ base_model: facebook/convnextv2-tiny-22k-384
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+ tags:
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+ - generated_from_trainer
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+ model-index:
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+ - name: CheXpert-5-convnextv2-tiny-384
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+ results: []
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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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+ # CheXpert-5-convnextv2-tiny-384
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+
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+ This model is a fine-tuned version of [facebook/convnextv2-tiny-22k-384](https://huggingface.co/facebook/convnextv2-tiny-22k-384) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.1009
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+ - Auroc Atelectasis: 0.7943
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+ - Auroc Cardiomegaly: 0.8187
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+ - Auroc Consolidation: 0.9269
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+ - Auroc Edema: 0.9233
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+ - Auroc Pleural effusion: 0.9315
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+ - Specificity Atelectasis: 0.7891
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+ - Specificity Cardiomegaly: 1.0
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+ - Specificity Consolidation: 0.9948
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+ - Specificity Edema: 0.8407
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+ - Specificity Pleural effusion: 0.8038
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+ - Exact Match: 0.4464
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+ - Hamming Distance: 0.1804
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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: 0.001
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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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+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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+ - lr_scheduler_type: cosine
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+ - lr_scheduler_warmup_steps: 2500
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+ - num_epochs: 6
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Auroc Atelectasis | Auroc Cardiomegaly | Auroc Consolidation | Auroc Edema | Auroc Pleural effusion | Specificity Atelectasis | Specificity Cardiomegaly | Specificity Consolidation | Specificity Edema | Specificity Pleural effusion | Exact Match | Hamming Distance |
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+ |:-------------:|:-----:|:-----:|:---------------:|:-----------------:|:------------------:|:-------------------:|:-----------:|:----------------------:|:-----------------------:|:------------------------:|:-------------------------:|:-----------------:|:----------------------------:|:-----------:|:----------------:|
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+ | 0.0891 | 1.0 | 6120 | 0.0893 | 0.7323 | 0.8366 | 0.7020 | 0.8387 | 0.8702 | 0.4510 | 0.9661 | 1.0 | 0.6596 | 0.5392 | 0.2616 | 0.2444 |
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+ | 0.0854 | 2.0 | 12240 | 0.0831 | 0.7535 | 0.8556 | 0.7350 | 0.8651 | 0.8881 | 0.7293 | 0.9042 | 0.9936 | 0.7083 | 0.6259 | 0.3571 | 0.1973 |
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+ | 0.082 | 3.0 | 18360 | 0.0824 | 0.7683 | 0.8696 | 0.7473 | 0.8720 | 0.8961 | 0.6956 | 0.8196 | 0.9881 | 0.6087 | 0.6611 | 0.3298 | 0.2177 |
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+ | 0.0799 | 4.0 | 24480 | 0.0802 | 0.7749 | 0.8720 | 0.7562 | 0.8783 | 0.9005 | 0.7450 | 0.8831 | 0.9608 | 0.7341 | 0.6984 | 0.3802 | 0.1880 |
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+ | 0.0759 | 5.0 | 30600 | 0.0793 | 0.7795 | 0.8746 | 0.7583 | 0.8818 | 0.9030 | 0.7277 | 0.8948 | 0.9711 | 0.7618 | 0.7045 | 0.3869 | 0.1823 |
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+ | 0.0739 | 6.0 | 36720 | 0.0798 | 0.7787 | 0.8727 | 0.7561 | 0.8812 | 0.9031 | 0.7461 | 0.8921 | 0.9690 | 0.7487 | 0.7074 | 0.3886 | 0.1824 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.41.0
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+ - Pytorch 2.1.2
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+ - Datasets 2.19.1
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+ - Tokenizers 0.19.1
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