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# vit-base-kidney-stone-4-Michel_Daudon_-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: 0.5183
- Accuracy: 0.8333
- Precision: 0.8596
- Recall: 0.8333
- F1: 0.8313

## 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     |
|:-------------:|:-------:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.4337        | 0.1667  | 100  | 0.6415          | 0.7688   | 0.7866    | 0.7688 | 0.7620 |
| 0.5458        | 0.3333  | 200  | 1.0270          | 0.7204   | 0.8072    | 0.7204 | 0.6929 |
| 0.1893        | 0.5     | 300  | 0.5183          | 0.8333   | 0.8596    | 0.8333 | 0.8313 |
| 0.2041        | 0.6667  | 400  | 0.5611          | 0.8333   | 0.8651    | 0.8333 | 0.8360 |
| 0.2087        | 0.8333  | 500  | 0.8036          | 0.7846   | 0.8253    | 0.7846 | 0.7916 |
| 0.1888        | 1.0     | 600  | 0.7427          | 0.8046   | 0.8312    | 0.8046 | 0.7960 |
| 0.1175        | 1.1667  | 700  | 0.7927          | 0.7837   | 0.7906    | 0.7837 | 0.7770 |
| 0.5783        | 1.3333  | 800  | 0.9454          | 0.7521   | 0.8095    | 0.7521 | 0.7551 |
| 0.1242        | 1.5     | 900  | 1.0772          | 0.7704   | 0.8102    | 0.7704 | 0.7796 |
| 0.1045        | 1.6667  | 1000 | 0.8234          | 0.8296   | 0.8333    | 0.8296 | 0.8223 |
| 0.1007        | 1.8333  | 1100 | 1.1756          | 0.7546   | 0.7483    | 0.7546 | 0.7460 |
| 0.0101        | 2.0     | 1200 | 0.7921          | 0.8446   | 0.8782    | 0.8446 | 0.8486 |
| 0.0079        | 2.1667  | 1300 | 0.9626          | 0.8204   | 0.8644    | 0.8204 | 0.8241 |
| 0.0626        | 2.3333  | 1400 | 1.0140          | 0.8025   | 0.8441    | 0.8025 | 0.8040 |
| 0.0216        | 2.5     | 1500 | 0.9297          | 0.8358   | 0.8540    | 0.8358 | 0.8364 |
| 0.0707        | 2.6667  | 1600 | 0.9193          | 0.8196   | 0.8425    | 0.8196 | 0.8203 |
| 0.0308        | 2.8333  | 1700 | 0.9988          | 0.8246   | 0.8429    | 0.8246 | 0.8209 |
| 0.0863        | 3.0     | 1800 | 0.8083          | 0.83     | 0.8592    | 0.83   | 0.8332 |
| 0.0016        | 3.1667  | 1900 | 1.1933          | 0.8029   | 0.8475    | 0.8029 | 0.8079 |
| 0.0014        | 3.3333  | 2000 | 1.0995          | 0.8142   | 0.8376    | 0.8142 | 0.8132 |
| 0.0745        | 3.5     | 2100 | 1.0348          | 0.8154   | 0.8720    | 0.8154 | 0.8259 |
| 0.0226        | 3.6667  | 2200 | 0.8861          | 0.8275   | 0.8576    | 0.8275 | 0.8303 |
| 0.0159        | 3.8333  | 2300 | 1.1476          | 0.79     | 0.8251    | 0.79   | 0.7981 |
| 0.1398        | 4.0     | 2400 | 1.2559          | 0.7879   | 0.8284    | 0.7879 | 0.7845 |
| 0.0011        | 4.1667  | 2500 | 1.2795          | 0.8008   | 0.8419    | 0.8008 | 0.8061 |
| 0.0016        | 4.3333  | 2600 | 1.1345          | 0.8108   | 0.8472    | 0.8108 | 0.8154 |
| 0.001         | 4.5     | 2700 | 1.0013          | 0.8242   | 0.8419    | 0.8242 | 0.8220 |
| 0.0888        | 4.6667  | 2800 | 1.0708          | 0.8313   | 0.8614    | 0.8313 | 0.8357 |
| 0.0212        | 4.8333  | 2900 | 1.1488          | 0.8113   | 0.8435    | 0.8113 | 0.8123 |
| 0.0857        | 5.0     | 3000 | 1.0805          | 0.8113   | 0.8506    | 0.8113 | 0.8182 |
| 0.0029        | 5.1667  | 3100 | 0.8731          | 0.8588   | 0.8762    | 0.8588 | 0.8619 |
| 0.0226        | 5.3333  | 3200 | 1.2513          | 0.8113   | 0.8410    | 0.8113 | 0.8128 |
| 0.0627        | 5.5     | 3300 | 1.1715          | 0.8063   | 0.8394    | 0.8063 | 0.8066 |
| 0.1471        | 5.6667  | 3400 | 0.8260          | 0.8325   | 0.8434    | 0.8325 | 0.8341 |
| 0.0008        | 5.8333  | 3500 | 0.8541          | 0.8404   | 0.8636    | 0.8404 | 0.8430 |
| 0.0005        | 6.0     | 3600 | 1.1119          | 0.8129   | 0.8340    | 0.8129 | 0.8165 |
| 0.0005        | 6.1667  | 3700 | 1.6586          | 0.7754   | 0.8261    | 0.7754 | 0.7762 |
| 0.0693        | 6.3333  | 3800 | 1.2959          | 0.8067   | 0.8427    | 0.8067 | 0.8107 |
| 0.0007        | 6.5     | 3900 | 1.0675          | 0.8142   | 0.8195    | 0.8142 | 0.8140 |
| 0.0008        | 6.6667  | 4000 | 1.3692          | 0.7904   | 0.8078    | 0.7904 | 0.7903 |
| 0.0063        | 6.8333  | 4100 | 1.2463          | 0.8092   | 0.8326    | 0.8092 | 0.8073 |
| 0.0006        | 7.0     | 4200 | 1.2368          | 0.8171   | 0.8433    | 0.8171 | 0.8187 |
| 0.0014        | 7.1667  | 4300 | 1.2245          | 0.7979   | 0.8126    | 0.7979 | 0.8004 |
| 0.0005        | 7.3333  | 4400 | 1.2486          | 0.7996   | 0.8134    | 0.7996 | 0.7996 |
| 0.0793        | 7.5     | 4500 | 1.3575          | 0.7762   | 0.8005    | 0.7762 | 0.7696 |
| 0.0006        | 7.6667  | 4600 | 1.2693          | 0.8013   | 0.8151    | 0.8013 | 0.7996 |
| 0.0005        | 7.8333  | 4700 | 1.1999          | 0.8192   | 0.8405    | 0.8192 | 0.8199 |
| 0.0007        | 8.0     | 4800 | 1.0169          | 0.8346   | 0.8517    | 0.8346 | 0.8353 |
| 0.067         | 8.1667  | 4900 | 1.0823          | 0.8346   | 0.8602    | 0.8346 | 0.8325 |
| 0.0007        | 8.3333  | 5000 | 1.3014          | 0.7996   | 0.8439    | 0.7996 | 0.7978 |
| 0.0003        | 8.5     | 5100 | 1.3176          | 0.7954   | 0.8398    | 0.7954 | 0.7986 |
| 0.0003        | 8.6667  | 5200 | 1.2994          | 0.8113   | 0.8559    | 0.8113 | 0.8124 |
| 0.0002        | 8.8333  | 5300 | 1.3460          | 0.7937   | 0.8308    | 0.7937 | 0.7908 |
| 0.0003        | 9.0     | 5400 | 1.0408          | 0.8346   | 0.8541    | 0.8346 | 0.8363 |
| 0.0002        | 9.1667  | 5500 | 1.1659          | 0.8246   | 0.8651    | 0.8246 | 0.8258 |
| 0.0002        | 9.3333  | 5600 | 1.1821          | 0.8263   | 0.8657    | 0.8263 | 0.8270 |
| 0.0002        | 9.5     | 5700 | 1.2786          | 0.8233   | 0.8607    | 0.8233 | 0.8227 |
| 0.0002        | 9.6667  | 5800 | 1.2611          | 0.8217   | 0.8577    | 0.8217 | 0.8210 |
| 0.0002        | 9.8333  | 5900 | 1.2556          | 0.8213   | 0.8568    | 0.8213 | 0.8206 |
| 0.0002        | 10.0    | 6000 | 1.3472          | 0.8158   | 0.8491    | 0.8158 | 0.8158 |
| 0.0002        | 10.1667 | 6100 | 1.3345          | 0.8175   | 0.8502    | 0.8175 | 0.8176 |
| 0.0001        | 10.3333 | 6200 | 1.3366          | 0.8187   | 0.8512    | 0.8187 | 0.8188 |
| 0.0001        | 10.5    | 6300 | 1.3363          | 0.8171   | 0.8497    | 0.8171 | 0.8174 |
| 0.0001        | 10.6667 | 6400 | 1.3340          | 0.8196   | 0.8517    | 0.8196 | 0.8198 |
| 0.0001        | 10.8333 | 6500 | 1.3658          | 0.8233   | 0.8593    | 0.8233 | 0.8243 |
| 0.0001        | 11.0    | 6600 | 1.3709          | 0.8237   | 0.8595    | 0.8237 | 0.8247 |
| 0.0001        | 11.1667 | 6700 | 1.3652          | 0.8242   | 0.8585    | 0.8242 | 0.8249 |
| 0.0001        | 11.3333 | 6800 | 1.3703          | 0.825    | 0.8594    | 0.825  | 0.8258 |
| 0.0001        | 11.5    | 6900 | 1.3755          | 0.8237   | 0.8579    | 0.8237 | 0.8247 |
| 0.0001        | 11.6667 | 7000 | 1.3781          | 0.8237   | 0.8579    | 0.8237 | 0.8247 |
| 0.0001        | 11.8333 | 7100 | 1.3811          | 0.8242   | 0.8582    | 0.8242 | 0.8251 |
| 0.0001        | 12.0    | 7200 | 1.3851          | 0.8237   | 0.8578    | 0.8237 | 0.8247 |
| 0.0001        | 12.1667 | 7300 | 1.3881          | 0.8242   | 0.8580    | 0.8242 | 0.8251 |
| 0.0001        | 12.3333 | 7400 | 1.3910          | 0.8246   | 0.8580    | 0.8246 | 0.8257 |
| 0.0001        | 12.5    | 7500 | 1.3937          | 0.8246   | 0.8580    | 0.8246 | 0.8257 |
| 0.0001        | 12.6667 | 7600 | 1.3977          | 0.8246   | 0.8580    | 0.8246 | 0.8257 |
| 0.0001        | 12.8333 | 7700 | 1.3995          | 0.8246   | 0.8580    | 0.8246 | 0.8257 |
| 0.0001        | 13.0    | 7800 | 1.4021          | 0.8246   | 0.8580    | 0.8246 | 0.8257 |
| 0.0001        | 13.1667 | 7900 | 1.4048          | 0.8246   | 0.8580    | 0.8246 | 0.8257 |
| 0.0001        | 13.3333 | 8000 | 1.4074          | 0.8246   | 0.8580    | 0.8246 | 0.8257 |
| 0.0001        | 13.5    | 8100 | 1.4099          | 0.8246   | 0.8580    | 0.8246 | 0.8257 |
| 0.0001        | 13.6667 | 8200 | 1.4117          | 0.8246   | 0.8580    | 0.8246 | 0.8257 |
| 0.0001        | 13.8333 | 8300 | 1.4134          | 0.825    | 0.8582    | 0.825  | 0.8261 |
| 0.0001        | 14.0    | 8400 | 1.4150          | 0.825    | 0.8582    | 0.825  | 0.8261 |
| 0.0001        | 14.1667 | 8500 | 1.4164          | 0.8246   | 0.8578    | 0.8246 | 0.8258 |
| 0.0001        | 14.3333 | 8600 | 1.4176          | 0.8242   | 0.8574    | 0.8242 | 0.8254 |
| 0.0001        | 14.5    | 8700 | 1.4186          | 0.8242   | 0.8574    | 0.8242 | 0.8254 |
| 0.0001        | 14.6667 | 8800 | 1.4192          | 0.8242   | 0.8574    | 0.8242 | 0.8254 |
| 0.0001        | 14.8333 | 8900 | 1.4197          | 0.8242   | 0.8574    | 0.8242 | 0.8254 |
| 0.0001        | 15.0    | 9000 | 1.4200          | 0.8242   | 0.8574    | 0.8242 | 0.8254 |


### Framework versions

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

mix-subtype_iva mix-subtype_iva2 mix-subtype_ivc mix-subtype_ivd mix-subtype_ia mix-subtype_va