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# vit-base-kidney-stone-3-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: 0.6275
- Accuracy: 0.8742
- Precision: 0.8819
- Recall: 0.8742
- F1: 0.8750

## 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     |
|:-------------:|:-------:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.3615        | 0.1667  | 100  | 0.7152          | 0.7458   | 0.8206    | 0.7458 | 0.7378 |
| 0.2196        | 0.3333  | 200  | 0.6798          | 0.775    | 0.8188    | 0.775  | 0.7769 |
| 0.2042        | 0.5     | 300  | 0.6700          | 0.7971   | 0.8383    | 0.7971 | 0.8057 |
| 0.177         | 0.6667  | 400  | 0.7327          | 0.8092   | 0.8387    | 0.8092 | 0.8142 |
| 0.2132        | 0.8333  | 500  | 0.7204          | 0.8054   | 0.8224    | 0.8054 | 0.8087 |
| 0.4081        | 1.0     | 600  | 0.8022          | 0.8067   | 0.8246    | 0.8067 | 0.8045 |
| 0.138         | 1.1667  | 700  | 0.7309          | 0.82     | 0.8416    | 0.82   | 0.8224 |
| 0.0145        | 1.3333  | 800  | 0.6764          | 0.8367   | 0.8514    | 0.8367 | 0.8408 |
| 0.0566        | 1.5     | 900  | 0.7420          | 0.8192   | 0.8387    | 0.8192 | 0.8223 |
| 0.0072        | 1.6667  | 1000 | 0.6850          | 0.8313   | 0.8399    | 0.8313 | 0.8328 |
| 0.0273        | 1.8333  | 1100 | 1.0173          | 0.8013   | 0.7947    | 0.8013 | 0.7908 |
| 0.0378        | 2.0     | 1200 | 0.7624          | 0.83     | 0.8341    | 0.83   | 0.8281 |
| 0.01          | 2.1667  | 1300 | 1.0041          | 0.7971   | 0.8459    | 0.7971 | 0.7972 |
| 0.2192        | 2.3333  | 1400 | 0.9177          | 0.81     | 0.8593    | 0.81   | 0.8109 |
| 0.045         | 2.5     | 1500 | 0.9214          | 0.8008   | 0.8468    | 0.8008 | 0.8065 |
| 0.0032        | 2.6667  | 1600 | 0.8712          | 0.8171   | 0.8436    | 0.8171 | 0.8208 |
| 0.134         | 2.8333  | 1700 | 0.9849          | 0.8129   | 0.8288    | 0.8129 | 0.8129 |
| 0.0571        | 3.0     | 1800 | 1.0024          | 0.8175   | 0.8620    | 0.8175 | 0.8214 |
| 0.0015        | 3.1667  | 1900 | 0.6275          | 0.8742   | 0.8819    | 0.8742 | 0.8750 |
| 0.0013        | 3.3333  | 2000 | 0.8558          | 0.84     | 0.8442    | 0.84   | 0.8409 |
| 0.1176        | 3.5     | 2100 | 0.9387          | 0.8379   | 0.8570    | 0.8379 | 0.8375 |
| 0.0081        | 3.6667  | 2200 | 1.3262          | 0.7858   | 0.8560    | 0.7858 | 0.7928 |
| 0.0012        | 3.8333  | 2300 | 1.2201          | 0.8033   | 0.8241    | 0.8033 | 0.8030 |
| 0.0018        | 4.0     | 2400 | 0.9460          | 0.8325   | 0.8694    | 0.8325 | 0.8389 |
| 0.0412        | 4.1667  | 2500 | 0.9619          | 0.8387   | 0.8617    | 0.8387 | 0.8425 |
| 0.0013        | 4.3333  | 2600 | 1.3212          | 0.8037   | 0.8370    | 0.8037 | 0.8037 |
| 0.011         | 4.5     | 2700 | 1.1590          | 0.8113   | 0.8201    | 0.8113 | 0.8085 |
| 0.0835        | 4.6667  | 2800 | 1.0838          | 0.8154   | 0.8495    | 0.8154 | 0.8194 |
| 0.162         | 4.8333  | 2900 | 1.1564          | 0.8071   | 0.8309    | 0.8071 | 0.8045 |
| 0.0013        | 5.0     | 3000 | 1.1460          | 0.785    | 0.8074    | 0.785  | 0.7915 |
| 0.0043        | 5.1667  | 3100 | 0.7268          | 0.8371   | 0.8578    | 0.8371 | 0.8383 |
| 0.0064        | 5.3333  | 3200 | 1.1635          | 0.8163   | 0.8599    | 0.8163 | 0.8171 |
| 0.0669        | 5.5     | 3300 | 1.1532          | 0.8008   | 0.8245    | 0.8008 | 0.8030 |
| 0.0009        | 5.6667  | 3400 | 0.9171          | 0.8342   | 0.8579    | 0.8342 | 0.8309 |
| 0.0307        | 5.8333  | 3500 | 1.0002          | 0.8333   | 0.8535    | 0.8333 | 0.8355 |
| 0.037         | 6.0     | 3600 | 1.1057          | 0.7979   | 0.8193    | 0.7979 | 0.8046 |
| 0.0008        | 6.1667  | 3700 | 0.9506          | 0.8342   | 0.8477    | 0.8342 | 0.8336 |
| 0.0039        | 6.3333  | 3800 | 0.9781          | 0.8317   | 0.8335    | 0.8317 | 0.8293 |
| 0.0006        | 6.5     | 3900 | 0.9525          | 0.8554   | 0.8659    | 0.8554 | 0.8510 |
| 0.0204        | 6.6667  | 4000 | 0.8203          | 0.8558   | 0.8536    | 0.8558 | 0.8535 |
| 0.0007        | 6.8333  | 4100 | 1.0635          | 0.8392   | 0.8640    | 0.8392 | 0.8346 |
| 0.0364        | 7.0     | 4200 | 0.8218          | 0.8508   | 0.8667    | 0.8508 | 0.8495 |
| 0.0011        | 7.1667  | 4300 | 1.1496          | 0.8217   | 0.8489    | 0.8217 | 0.8214 |
| 0.0754        | 7.3333  | 4400 | 0.7383          | 0.8521   | 0.8567    | 0.8521 | 0.8509 |
| 0.0007        | 7.5     | 4500 | 1.0083          | 0.8246   | 0.8397    | 0.8246 | 0.8216 |
| 0.0005        | 7.6667  | 4600 | 0.8850          | 0.8458   | 0.8587    | 0.8458 | 0.8456 |
| 0.0004        | 7.8333  | 4700 | 0.8987          | 0.8488   | 0.8621    | 0.8488 | 0.8483 |
| 0.0067        | 8.0     | 4800 | 0.8969          | 0.8421   | 0.8541    | 0.8421 | 0.8432 |
| 0.0003        | 8.1667  | 4900 | 1.1115          | 0.8171   | 0.8233    | 0.8171 | 0.8175 |
| 0.0002        | 8.3333  | 5000 | 1.1313          | 0.8154   | 0.8225    | 0.8154 | 0.8165 |
| 0.0004        | 8.5     | 5100 | 1.5668          | 0.8017   | 0.8439    | 0.8017 | 0.7970 |
| 0.0003        | 8.6667  | 5200 | 1.2458          | 0.8237   | 0.8579    | 0.8237 | 0.8247 |
| 0.0009        | 8.8333  | 5300 | 1.1443          | 0.815    | 0.8376    | 0.815  | 0.8158 |
| 0.0014        | 9.0     | 5400 | 1.3838          | 0.8092   | 0.8375    | 0.8092 | 0.8114 |
| 0.0554        | 9.1667  | 5500 | 1.2331          | 0.8108   | 0.8576    | 0.8108 | 0.8192 |
| 0.0003        | 9.3333  | 5600 | 0.9874          | 0.8504   | 0.8658    | 0.8504 | 0.8529 |
| 0.0003        | 9.5     | 5700 | 0.9882          | 0.8488   | 0.8602    | 0.8488 | 0.8514 |
| 0.0002        | 9.6667  | 5800 | 1.0519          | 0.8492   | 0.8653    | 0.8492 | 0.8524 |
| 0.0002        | 9.8333  | 5900 | 1.1310          | 0.8371   | 0.8587    | 0.8371 | 0.8414 |
| 0.0002        | 10.0    | 6000 | 1.1190          | 0.8333   | 0.8570    | 0.8333 | 0.8387 |
| 0.0002        | 10.1667 | 6100 | 1.1356          | 0.8333   | 0.8547    | 0.8333 | 0.8388 |
| 0.0002        | 10.3333 | 6200 | 1.2443          | 0.8279   | 0.8492    | 0.8279 | 0.8304 |
| 0.0002        | 10.5    | 6300 | 1.2286          | 0.8246   | 0.8534    | 0.8246 | 0.8304 |
| 0.0002        | 10.6667 | 6400 | 1.2313          | 0.8275   | 0.8508    | 0.8275 | 0.8319 |
| 0.0002        | 10.8333 | 6500 | 1.2065          | 0.8283   | 0.8377    | 0.8283 | 0.8289 |
| 0.0002        | 11.0    | 6600 | 1.3052          | 0.8046   | 0.8181    | 0.8046 | 0.8056 |
| 0.0001        | 11.1667 | 6700 | 1.2192          | 0.8233   | 0.8403    | 0.8233 | 0.8270 |
| 0.0002        | 11.3333 | 6800 | 1.2350          | 0.8233   | 0.8331    | 0.8233 | 0.8261 |
| 0.0013        | 11.5    | 6900 | 1.2510          | 0.8283   | 0.8474    | 0.8283 | 0.8317 |
| 0.004         | 11.6667 | 7000 | 1.4225          | 0.8075   | 0.8197    | 0.8075 | 0.8082 |
| 0.0002        | 11.8333 | 7100 | 1.5583          | 0.7904   | 0.8012    | 0.7904 | 0.7876 |
| 0.0003        | 12.0    | 7200 | 1.7201          | 0.7696   | 0.7996    | 0.7696 | 0.7696 |
| 0.0001        | 12.1667 | 7300 | 1.4283          | 0.8075   | 0.8297    | 0.8075 | 0.8113 |
| 0.0001        | 12.3333 | 7400 | 1.2310          | 0.8246   | 0.8425    | 0.8246 | 0.8280 |
| 0.0001        | 12.5    | 7500 | 1.2366          | 0.8279   | 0.8447    | 0.8279 | 0.8309 |
| 0.0002        | 12.6667 | 7600 | 1.2410          | 0.8279   | 0.8448    | 0.8279 | 0.8309 |
| 0.0001        | 12.8333 | 7700 | 1.2434          | 0.8287   | 0.8457    | 0.8287 | 0.8317 |
| 0.0001        | 13.0    | 7800 | 1.2539          | 0.8263   | 0.8438    | 0.8263 | 0.8293 |
| 0.0001        | 13.1667 | 7900 | 1.2479          | 0.8287   | 0.8444    | 0.8287 | 0.8313 |
| 0.0001        | 13.3333 | 8000 | 1.2510          | 0.8292   | 0.8449    | 0.8292 | 0.8317 |
| 0.0001        | 13.5    | 8100 | 1.2544          | 0.8296   | 0.8451    | 0.8296 | 0.8321 |
| 0.0001        | 13.6667 | 8200 | 1.2575          | 0.8296   | 0.8452    | 0.8296 | 0.8321 |
| 0.0001        | 13.8333 | 8300 | 1.2597          | 0.8296   | 0.8452    | 0.8296 | 0.8321 |
| 0.0001        | 14.0    | 8400 | 1.2618          | 0.8292   | 0.8447    | 0.8292 | 0.8316 |
| 0.0001        | 14.1667 | 8500 | 1.2632          | 0.8292   | 0.8447    | 0.8292 | 0.8316 |
| 0.0001        | 14.3333 | 8600 | 1.2651          | 0.8292   | 0.8447    | 0.8292 | 0.8316 |
| 0.0001        | 14.5    | 8700 | 1.2662          | 0.8292   | 0.8447    | 0.8292 | 0.8316 |
| 0.0001        | 14.6667 | 8800 | 1.2672          | 0.8292   | 0.8447    | 0.8292 | 0.8316 |
| 0.0001        | 14.8333 | 8900 | 1.2678          | 0.8292   | 0.8447    | 0.8292 | 0.8316 |
| 0.0001        | 15.0    | 9000 | 1.2680          | 0.8292   | 0.8447    | 0.8292 | 0.8316 |


### 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