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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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- image-classification |
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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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<!-- 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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# CheXpert-5-convnextv2-tiny-384 |
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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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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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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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### Training results |
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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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### Framework versions |
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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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