
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# CheXpert-5-convnextv2-tiny-384

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.
It achieves the following results on the evaluation set:
- Loss: 0.1644
- Auroc Atelectasis: 0.4756
- Auroc Cardiomegaly: 0.6956
- Auroc Consolidation: 0.5969
- Auroc Edema: 0.8883
- Auroc Pleural effusion: 0.8692
- Specificity Atelectasis: 0.0816
- Specificity Cardiomegaly: 0.7215
- Specificity Consolidation: 0.7068
- Specificity Edema: 0.4835
- Specificity Pleural effusion: 0.2532
- Exact Match: 0.0402
- Hamming Distance: 0.4554

## 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: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- 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 |
|:-------------:|:-----:|:-----:|:---------------:|:-----------------:|:------------------:|:-------------------:|:-----------:|:----------------------:|:-----------------------:|:------------------------:|:-------------------------:|:-----------------:|:----------------------------:|:-----------:|:----------------:|
| 0.1201        | 1.0   | 2010  | 0.1180          | 0.7583            | 0.8187             | 0.6532              | 0.8171      | 0.8295                 | 0.1447                  | 0.4273                   | 0.9971                    | 0.3333            | 0.0811                       | 0.1346      | 0.3061           |
| 0.1177        | 2.0   | 4020  | 0.1176          | 0.7586            | 0.8387             | 0.6655              | 0.8196      | 0.8411                 | 0.3666                  | 0.6803                   | 0.7962                    | 0.3031            | 0.2830                       | 0.1541      | 0.2769           |
| 0.1145        | 3.0   | 6030  | 0.1124          | 0.7736            | 0.8423             | 0.6789              | 0.8345      | 0.8541                 | 0.4841                  | 0.6914                   | 0.9640                    | 0.2092            | 0.2477                       | 0.2013      | 0.2523           |
| 0.1098        | 4.0   | 8040  | 0.1094          | 0.7852            | 0.8619             | 0.6923              | 0.8407      | 0.8629                 | 0.3826                  | 0.8147                   | 0.7786                    | 0.3836            | 0.1550                       | 0.1719      | 0.2590           |
| 0.104         | 5.0   | 10050 | 0.1062          | 0.7904            | 0.8632             | 0.7045              | 0.8515      | 0.8736                 | 0.4176                  | 0.7128                   | 0.8683                    | 0.3822            | 0.2096                       | 0.1955      | 0.2496           |
| 0.0984        | 6.0   | 12060 | 0.1061          | 0.7944            | 0.8652             | 0.7057              | 0.8536      | 0.8741                 | 0.4495                  | 0.7491                   | 0.8963                    | 0.4333            | 0.2879                       | 0.2398      | 0.2349           |


### Framework versions

- Transformers 4.48.3
- Pytorch 2.1.2
- Datasets 3.3.0
- Tokenizers 0.21.0

atelectasis cardiomegaly consolidation edema pleural effusion