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# lung-cancer-image-classification

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 imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0177
- Precision: 0.9963
- Recall: 0.9963
- F1: 0.9963
- Accuracy: 0.9963
- Confusion matrix: 1245	1	4
0	1250	0
9	0	1241

## 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: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy | Confusion matrix              |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|:-----------------------------:|
| 0.3173        | 0.21  | 100  | 0.1952          | 0.9371    | 0.9331 | 0.9339 | 0.9331   | 1186	0	64
90	1160	0
97	0	1153 |
| 0.1312        | 0.43  | 200  | 0.0752          | 0.9786    | 0.9779 | 0.9778 | 0.9779   | 1178	1	71
2	1248	0
9	0	1241   |
| 0.1453        | 0.64  | 300  | 0.0688          | 0.9759    | 0.9752 | 0.9752 | 0.9752   | 1232	1	17
8	1242	0
67	0	1183  |
| 0.0146        | 0.85  | 400  | 0.0485          | 0.9854    | 0.9853 | 0.9853 | 0.9853   | 1212	2	36
0	1250	0
17	0	1233  |
| 0.0075        | 1.07  | 500  | 0.0376          | 0.9897    | 0.9896 | 0.9896 | 0.9896   | 1220	1	29
5	1245	0
4	0	1246   |
| 0.054         | 1.28  | 600  | 0.0233          | 0.9939    | 0.9939 | 0.9939 | 0.9939   | 1241	1	8
0	1250	0
14	0	1236   |
| 0.0272        | 1.49  | 700  | 0.0156          | 0.9950    | 0.9949 | 0.9949 | 0.9949   | 1235	1	14
0	1250	0
4	0	1246   |
| 0.0307        | 1.71  | 800  | 0.0172          | 0.9949    | 0.9949 | 0.9949 | 0.9949   | 1244	1	5
0	1250	0
13	0	1237   |
| 0.0022        | 1.92  | 900  | 0.0144          | 0.9963    | 0.9963 | 0.9963 | 0.9963   | 1237	1	12
0	1250	0
1	0	1249   |
| 0.0015        | 2.13  | 1000 | 0.0156          | 0.9963    | 0.9963 | 0.9963 | 0.9963   | 1238	1	11
0	1250	0
2	0	1248   |
| 0.0014        | 2.35  | 1100 | 0.0138          | 0.9971    | 0.9971 | 0.9971 | 0.9971   | 1243	1	6
0	1250	0
4	0	1246    |
| 0.0317        | 2.56  | 1200 | 0.0110          | 0.9973    | 0.9973 | 0.9973 | 0.9973   | 1244	1	5
0	1250	0
4	0	1246    |
| 0.0011        | 2.77  | 1300 | 0.0159          | 0.9963    | 0.9963 | 0.9963 | 0.9963   | 1236	1	13
0	1250	0
0	0	1250   |
| 0.0012        | 2.99  | 1400 | 0.0120          | 0.9971    | 0.9971 | 0.9971 | 0.9971   | 1239	1	10
0	1250	0
0	0	1250   |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.19.0
- Tokenizers 0.15.2

lung_aca lung_n lung_scc