lung-cancer-image-classification
This model is a fine-tuned version of 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
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Base model
google/vit-base-patch16-224-in21kEvaluation results
- Precision on imagefolderself-reported0.996
- Recall on imagefolderself-reported0.996
- F1 on imagefolderself-reported0.996
- Accuracy on imagefolderself-reported0.996