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---
license: apache-2.0
tags:
- image-classification
- generated_from_trainer
datasets:
- chest xrays
widget:
- src: https://drive.google.com/uc?id=1yqnhD4Wjt4Y_NGLtijTGGaaw9GL497kQ
example_title: PNEUMONIA
- src: https://drive.google.com/uc?id=1xjcIEDb8kuSd4wF44gCEgsc0PfRvs53m
example_title: NORMAL
metrics:
- accuracy
model-index:
- name: vit-base-xray-pneumonia
results: []
---
<!-- 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. -->
# vit-base-xray-pneumonia
This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the [chest-xray-pneumonia](https://www.kaggle.com/paultimothymooney/chest-xray-pneumonia) dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3387
- Accuracy: 0.9006
## 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: 0.0002
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.1233 | 0.31 | 100 | 1.1662 | 0.6651 |
| 0.0868 | 0.61 | 200 | 0.3387 | 0.9006 |
| 0.1387 | 0.92 | 300 | 0.5297 | 0.8237 |
| 0.1264 | 1.23 | 400 | 0.4566 | 0.8590 |
| 0.0829 | 1.53 | 500 | 0.6832 | 0.8285 |
| 0.0734 | 1.84 | 600 | 0.4886 | 0.8157 |
| 0.0132 | 2.15 | 700 | 1.3639 | 0.7292 |
| 0.0877 | 2.45 | 800 | 0.5258 | 0.8846 |
| 0.0516 | 2.76 | 900 | 0.8772 | 0.8013 |
| 0.0637 | 3.07 | 1000 | 0.4947 | 0.8558 |
| 0.0022 | 3.37 | 1100 | 1.0062 | 0.8045 |
| 0.0555 | 3.68 | 1200 | 0.7822 | 0.8285 |
| 0.0405 | 3.99 | 1300 | 1.9288 | 0.6779 |
| 0.0012 | 4.29 | 1400 | 1.2153 | 0.7981 |
| 0.0034 | 4.6 | 1500 | 1.8931 | 0.7308 |
| 0.0339 | 4.91 | 1600 | 0.9071 | 0.8590 |
| 0.0013 | 5.21 | 1700 | 1.6266 | 0.7580 |
| 0.0373 | 5.52 | 1800 | 1.5252 | 0.7676 |
| 0.001 | 5.83 | 1900 | 1.2748 | 0.7869 |
| 0.0005 | 6.13 | 2000 | 1.2103 | 0.8061 |
| 0.0004 | 6.44 | 2100 | 1.3133 | 0.7981 |
| 0.0004 | 6.75 | 2200 | 1.2200 | 0.8045 |
| 0.0004 | 7.06 | 2300 | 1.2834 | 0.7933 |
| 0.0004 | 7.36 | 2400 | 1.3080 | 0.7949 |
| 0.0003 | 7.67 | 2500 | 1.3814 | 0.7917 |
| 0.0004 | 7.98 | 2600 | 1.2853 | 0.7965 |
| 0.0003 | 8.28 | 2700 | 1.3644 | 0.7933 |
| 0.0003 | 8.59 | 2800 | 1.3137 | 0.8013 |
| 0.0003 | 8.9 | 2900 | 1.3507 | 0.7997 |
| 0.0003 | 9.2 | 3000 | 1.3751 | 0.7997 |
| 0.0003 | 9.51 | 3100 | 1.3884 | 0.7981 |
| 0.0003 | 9.82 | 3200 | 1.3831 | 0.7997 |
## Example Images
#### Pneumonia Chest X-Ray
#### Normal Chest X-Ray
### Framework versions
- Transformers 4.17.0
- Pytorch 1.10.0+cu111
- Datasets 1.18.4
- Tokenizers 0.11.6
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