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# vit-base-kidney-stone-5-Jonathan_El-Beze_-w256_1k_v1-_MIX

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: 0.4482
- Accuracy: 0.8683
- Precision: 0.8788
- Recall: 0.8683
- F1: 0.8688

## 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: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 15
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:-------:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.2457        | 0.1667  | 100  | 0.5382          | 0.8258   | 0.8382    | 0.8258 | 0.8180 |
| 0.0854        | 0.3333  | 200  | 0.7377          | 0.7875   | 0.8422    | 0.7875 | 0.7795 |
| 0.1279        | 0.5     | 300  | 0.6710          | 0.7883   | 0.8568    | 0.7883 | 0.7883 |
| 0.1442        | 0.6667  | 400  | 0.5535          | 0.8192   | 0.8342    | 0.8192 | 0.8192 |
| 0.2868        | 0.8333  | 500  | 1.0679          | 0.7242   | 0.7910    | 0.7242 | 0.7163 |
| 0.1327        | 1.0     | 600  | 0.4482          | 0.8683   | 0.8788    | 0.8683 | 0.8688 |
| 0.1097        | 1.1667  | 700  | 0.8910          | 0.7983   | 0.8425    | 0.7983 | 0.7898 |
| 0.0725        | 1.3333  | 800  | 0.6816          | 0.8037   | 0.8375    | 0.8037 | 0.8015 |
| 0.0152        | 1.5     | 900  | 0.8366          | 0.8175   | 0.8466    | 0.8175 | 0.8169 |
| 0.0057        | 1.6667  | 1000 | 0.5298          | 0.8812   | 0.8924    | 0.8812 | 0.8810 |
| 0.0804        | 1.8333  | 1100 | 1.1549          | 0.7425   | 0.8162    | 0.7425 | 0.7228 |
| 0.0655        | 2.0     | 1200 | 0.9445          | 0.795    | 0.8350    | 0.795  | 0.7907 |
| 0.1261        | 2.1667  | 1300 | 0.8882          | 0.8121   | 0.8449    | 0.8121 | 0.8067 |
| 0.0418        | 2.3333  | 1400 | 0.6411          | 0.8638   | 0.8682    | 0.8638 | 0.8636 |
| 0.0809        | 2.5     | 1500 | 0.5780          | 0.8708   | 0.8811    | 0.8708 | 0.8683 |
| 0.1062        | 2.6667  | 1600 | 1.1595          | 0.7875   | 0.8249    | 0.7875 | 0.7623 |
| 0.0021        | 2.8333  | 1700 | 1.4652          | 0.7525   | 0.8050    | 0.7525 | 0.7379 |
| 0.0031        | 3.0     | 1800 | 1.1441          | 0.7904   | 0.8277    | 0.7904 | 0.7647 |
| 0.0026        | 3.1667  | 1900 | 0.6132          | 0.8479   | 0.8537    | 0.8479 | 0.8471 |
| 0.0011        | 3.3333  | 2000 | 0.5269          | 0.8925   | 0.8948    | 0.8925 | 0.8913 |
| 0.0014        | 3.5     | 2100 | 0.8908          | 0.7808   | 0.8294    | 0.7808 | 0.7723 |
| 0.0013        | 3.6667  | 2200 | 0.8869          | 0.8075   | 0.8466    | 0.8075 | 0.8101 |
| 0.0007        | 3.8333  | 2300 | 0.6948          | 0.8667   | 0.8817    | 0.8667 | 0.8662 |
| 0.0824        | 4.0     | 2400 | 0.4991          | 0.8929   | 0.8962    | 0.8929 | 0.8934 |
| 0.0021        | 4.1667  | 2500 | 0.5147          | 0.9038   | 0.9116    | 0.9038 | 0.9025 |
| 0.0006        | 4.3333  | 2600 | 0.5748          | 0.8967   | 0.9043    | 0.8967 | 0.8970 |
| 0.0005        | 4.5     | 2700 | 0.5797          | 0.8962   | 0.9035    | 0.8962 | 0.8966 |
| 0.0006        | 4.6667  | 2800 | 0.8573          | 0.855    | 0.8741    | 0.855  | 0.8534 |
| 0.0006        | 4.8333  | 2900 | 0.7548          | 0.8446   | 0.8617    | 0.8446 | 0.8415 |
| 0.0019        | 5.0     | 3000 | 0.6473          | 0.8733   | 0.8850    | 0.8733 | 0.8714 |
| 0.0469        | 5.1667  | 3100 | 0.8790          | 0.8258   | 0.8368    | 0.8258 | 0.8274 |
| 0.0271        | 5.3333  | 3200 | 1.6532          | 0.7525   | 0.8328    | 0.7525 | 0.7430 |
| 0.0005        | 5.5     | 3300 | 0.7739          | 0.8654   | 0.8743    | 0.8654 | 0.8660 |
| 0.1697        | 5.6667  | 3400 | 0.7311          | 0.8592   | 0.8816    | 0.8592 | 0.8612 |
| 0.0162        | 5.8333  | 3500 | 0.7819          | 0.8621   | 0.8678    | 0.8621 | 0.8620 |
| 0.0039        | 6.0     | 3600 | 1.1462          | 0.8092   | 0.8282    | 0.8092 | 0.8073 |
| 0.0005        | 6.1667  | 3700 | 0.6625          | 0.8692   | 0.8750    | 0.8692 | 0.8699 |
| 0.0022        | 6.3333  | 3800 | 1.1395          | 0.8079   | 0.8245    | 0.8079 | 0.7988 |
| 0.0039        | 6.5     | 3900 | 0.5258          | 0.9104   | 0.9145    | 0.9104 | 0.9111 |
| 0.0003        | 6.6667  | 4000 | 0.8170          | 0.8438   | 0.8598    | 0.8438 | 0.8445 |
| 0.0005        | 6.8333  | 4100 | 0.6582          | 0.8862   | 0.8906    | 0.8862 | 0.8847 |
| 0.0003        | 7.0     | 4200 | 0.8093          | 0.8571   | 0.8707    | 0.8571 | 0.8585 |
| 0.0002        | 7.1667  | 4300 | 0.7803          | 0.8633   | 0.8744    | 0.8633 | 0.8645 |
| 0.0002        | 7.3333  | 4400 | 0.7809          | 0.865    | 0.8767    | 0.865  | 0.8660 |
| 0.0002        | 7.5     | 4500 | 0.7817          | 0.8671   | 0.8788    | 0.8671 | 0.8680 |
| 0.0002        | 7.6667  | 4600 | 0.7804          | 0.8683   | 0.8792    | 0.8683 | 0.8692 |
| 0.0001        | 7.8333  | 4700 | 0.7560          | 0.8762   | 0.8840    | 0.8762 | 0.8766 |
| 0.0002        | 8.0     | 4800 | 0.7634          | 0.8767   | 0.8848    | 0.8767 | 0.8771 |
| 0.0001        | 8.1667  | 4900 | 0.7603          | 0.8792   | 0.8866    | 0.8792 | 0.8794 |
| 0.0001        | 8.3333  | 5000 | 0.7596          | 0.8792   | 0.8864    | 0.8792 | 0.8794 |
| 0.0001        | 8.5     | 5100 | 0.7636          | 0.8804   | 0.8875    | 0.8804 | 0.8806 |
| 0.0001        | 8.6667  | 5200 | 0.7681          | 0.8792   | 0.8869    | 0.8792 | 0.8794 |
| 0.0001        | 8.8333  | 5300 | 0.7720          | 0.8796   | 0.8877    | 0.8796 | 0.8799 |
| 0.0001        | 9.0     | 5400 | 0.7743          | 0.8796   | 0.8876    | 0.8796 | 0.8798 |
| 0.0001        | 9.1667  | 5500 | 0.7771          | 0.88     | 0.8880    | 0.88   | 0.8802 |
| 0.0001        | 9.3333  | 5600 | 0.7801          | 0.8804   | 0.8883    | 0.8804 | 0.8806 |
| 0.0001        | 9.5     | 5700 | 0.7823          | 0.8804   | 0.8883    | 0.8804 | 0.8806 |
| 0.0001        | 9.6667  | 5800 | 0.7851          | 0.8808   | 0.8885    | 0.8808 | 0.8810 |
| 0.0001        | 9.8333  | 5900 | 0.7873          | 0.8808   | 0.8885    | 0.8808 | 0.8810 |
| 0.0001        | 10.0    | 6000 | 0.7907          | 0.8812   | 0.8890    | 0.8812 | 0.8814 |
| 0.0001        | 10.1667 | 6100 | 0.7934          | 0.8817   | 0.8893    | 0.8817 | 0.8818 |
| 0.0001        | 10.3333 | 6200 | 0.7968          | 0.8817   | 0.8896    | 0.8817 | 0.8818 |
| 0.0001        | 10.5    | 6300 | 0.8003          | 0.8817   | 0.8896    | 0.8817 | 0.8818 |
| 0.0001        | 10.6667 | 6400 | 0.8027          | 0.8817   | 0.8896    | 0.8817 | 0.8818 |
| 0.0001        | 10.8333 | 6500 | 0.8035          | 0.8812   | 0.8894    | 0.8812 | 0.8815 |
| 0.0001        | 11.0    | 6600 | 0.8049          | 0.8812   | 0.8894    | 0.8812 | 0.8815 |
| 0.0001        | 11.1667 | 6700 | 0.8070          | 0.8812   | 0.8894    | 0.8812 | 0.8815 |
| 0.0001        | 11.3333 | 6800 | 0.8091          | 0.8812   | 0.8894    | 0.8812 | 0.8815 |
| 0.0001        | 11.5    | 6900 | 0.8124          | 0.8817   | 0.8897    | 0.8817 | 0.8818 |
| 0.0001        | 11.6667 | 7000 | 0.8147          | 0.8817   | 0.8897    | 0.8817 | 0.8818 |
| 0.0001        | 11.8333 | 7100 | 0.8163          | 0.8821   | 0.8899    | 0.8821 | 0.8822 |
| 0.0001        | 12.0    | 7200 | 0.8181          | 0.8829   | 0.8908    | 0.8829 | 0.8830 |
| 0.0           | 12.1667 | 7300 | 0.8204          | 0.8833   | 0.8911    | 0.8833 | 0.8834 |
| 0.0           | 12.3333 | 7400 | 0.8224          | 0.8833   | 0.8911    | 0.8833 | 0.8834 |
| 0.0           | 12.5    | 7500 | 0.8246          | 0.8825   | 0.8902    | 0.8825 | 0.8826 |
| 0.0           | 12.6667 | 7600 | 0.8267          | 0.8821   | 0.8898    | 0.8821 | 0.8821 |
| 0.0           | 12.8333 | 7700 | 0.8280          | 0.8821   | 0.8898    | 0.8821 | 0.8821 |
| 0.0           | 13.0    | 7800 | 0.8290          | 0.8825   | 0.8902    | 0.8825 | 0.8826 |
| 0.0           | 13.1667 | 7900 | 0.8309          | 0.8821   | 0.8898    | 0.8821 | 0.8821 |
| 0.0           | 13.3333 | 8000 | 0.8328          | 0.8821   | 0.8898    | 0.8821 | 0.8821 |
| 0.0           | 13.5    | 8100 | 0.8340          | 0.8825   | 0.8902    | 0.8825 | 0.8826 |
| 0.0           | 13.6667 | 8200 | 0.8348          | 0.8821   | 0.8898    | 0.8821 | 0.8821 |
| 0.0           | 13.8333 | 8300 | 0.8360          | 0.8821   | 0.8898    | 0.8821 | 0.8821 |
| 0.0           | 14.0    | 8400 | 0.8369          | 0.8825   | 0.8902    | 0.8825 | 0.8826 |
| 0.0           | 14.1667 | 8500 | 0.8379          | 0.8821   | 0.8898    | 0.8821 | 0.8821 |
| 0.0           | 14.3333 | 8600 | 0.8386          | 0.8821   | 0.8898    | 0.8821 | 0.8821 |
| 0.0           | 14.5    | 8700 | 0.8390          | 0.8829   | 0.8905    | 0.8829 | 0.8830 |
| 0.0           | 14.6667 | 8800 | 0.8397          | 0.8825   | 0.8901    | 0.8825 | 0.8825 |
| 0.0           | 14.8333 | 8900 | 0.8401          | 0.8825   | 0.8901    | 0.8825 | 0.8825 |
| 0.0           | 15.0    | 9000 | 0.8401          | 0.8825   | 0.8901    | 0.8825 | 0.8825 |


### Framework versions

- Transformers 4.48.2
- Pytorch 2.6.0+cu126
- Datasets 3.1.0
- Tokenizers 0.21.0

mix-subtype_iiia mix-subtype_iia mix-subtype_ivc mix-subtype_ivd mix-subtype_ia mix-subtype_va