metadata
license: apache-2.0
base_model: facebook/convnextv2-tiny-22k-384
tags:
- image-classification
- generated_from_trainer
model-index:
- name: CheXpert-5-convnextv2-tiny-384
results: []
CheXpert-5-convnextv2-tiny-384
This model is a fine-tuned version of facebook/convnextv2-tiny-22k-384 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1009
- Auroc Atelectasis: 0.7943
- Auroc Cardiomegaly: 0.8187
- Auroc Consolidation: 0.9269
- Auroc Edema: 0.9233
- Auroc Pleural effusion: 0.9315
- Specificity Atelectasis: 0.7891
- Specificity Cardiomegaly: 1.0
- Specificity Consolidation: 0.9948
- Specificity Edema: 0.8407
- Specificity Pleural effusion: 0.8038
- Exact Match: 0.4464
- Hamming Distance: 0.1804
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.001
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 2500
- num_epochs: 6
Training results
| 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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 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 |
| 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 |
| 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 |
| 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 |
| 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 |
| 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 |
Framework versions
- Transformers 4.41.0
- Pytorch 2.1.2
- Datasets 2.19.1
- Tokenizers 0.19.1