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# vit-base-kidney-stone-5-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: 0.3946
- Accuracy: 0.8888
- Precision: 0.8975
- Recall: 0.8888
- F1: 0.8871

## 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     |
|:-------------:|:-------:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.5771        | 0.1667  | 100  | 0.6379          | 0.7929   | 0.8436    | 0.7929 | 0.7925 |
| 0.3294        | 0.3333  | 200  | 0.7346          | 0.7992   | 0.8342    | 0.7992 | 0.7915 |
| 0.5113        | 0.5     | 300  | 0.5429          | 0.8638   | 0.8829    | 0.8638 | 0.8625 |
| 0.1584        | 0.6667  | 400  | 0.6327          | 0.8304   | 0.8612    | 0.8304 | 0.8308 |
| 0.2638        | 0.8333  | 500  | 1.0157          | 0.7575   | 0.7964    | 0.7575 | 0.7623 |
| 0.2057        | 1.0     | 600  | 0.3946          | 0.8888   | 0.8975    | 0.8888 | 0.8871 |
| 0.1699        | 1.1667  | 700  | 0.7519          | 0.7987   | 0.8373    | 0.7987 | 0.8004 |
| 0.1526        | 1.3333  | 800  | 0.7253          | 0.8342   | 0.8727    | 0.8342 | 0.8372 |
| 0.0361        | 1.5     | 900  | 1.0151          | 0.7829   | 0.8064    | 0.7829 | 0.7748 |
| 0.0756        | 1.6667  | 1000 | 0.6614          | 0.8625   | 0.8860    | 0.8625 | 0.8647 |
| 0.0267        | 1.8333  | 1100 | 0.9163          | 0.8154   | 0.8321    | 0.8154 | 0.8195 |
| 0.1447        | 2.0     | 1200 | 0.7084          | 0.8271   | 0.8381    | 0.8271 | 0.8244 |
| 0.0132        | 2.1667  | 1300 | 0.8919          | 0.8354   | 0.8758    | 0.8354 | 0.8378 |
| 0.0254        | 2.3333  | 1400 | 0.7531          | 0.8488   | 0.8772    | 0.8488 | 0.8505 |
| 0.0848        | 2.5     | 1500 | 0.6491          | 0.8733   | 0.8841    | 0.8733 | 0.8765 |
| 0.0605        | 2.6667  | 1600 | 0.7045          | 0.855    | 0.8708    | 0.855  | 0.8515 |
| 0.0085        | 2.8333  | 1700 | 1.1652          | 0.7992   | 0.8305    | 0.7992 | 0.7879 |
| 0.1798        | 3.0     | 1800 | 0.9389          | 0.8075   | 0.8350    | 0.8075 | 0.8075 |
| 0.0555        | 3.1667  | 1900 | 0.7451          | 0.8421   | 0.8593    | 0.8421 | 0.8452 |
| 0.0245        | 3.3333  | 2000 | 0.4729          | 0.8888   | 0.8942    | 0.8888 | 0.8880 |
| 0.0017        | 3.5     | 2100 | 0.7608          | 0.8629   | 0.8859    | 0.8629 | 0.8663 |
| 0.0266        | 3.6667  | 2200 | 0.7795          | 0.8571   | 0.8668    | 0.8571 | 0.8578 |
| 0.0072        | 3.8333  | 2300 | 0.6487          | 0.8596   | 0.8862    | 0.8596 | 0.8600 |
| 0.0019        | 4.0     | 2400 | 0.6297          | 0.8712   | 0.8846    | 0.8712 | 0.8723 |
| 0.001         | 4.1667  | 2500 | 0.8346          | 0.8679   | 0.8849    | 0.8679 | 0.8692 |
| 0.0014        | 4.3333  | 2600 | 0.8441          | 0.8633   | 0.8869    | 0.8633 | 0.8671 |
| 0.0068        | 4.5     | 2700 | 0.7032          | 0.8662   | 0.8769    | 0.8662 | 0.8649 |
| 0.0014        | 4.6667  | 2800 | 0.7379          | 0.86     | 0.8795    | 0.86   | 0.8565 |
| 0.0951        | 4.8333  | 2900 | 0.5960          | 0.8979   | 0.9086    | 0.8979 | 0.8984 |
| 0.0439        | 5.0     | 3000 | 0.6975          | 0.8708   | 0.8902    | 0.8708 | 0.8699 |
| 0.1022        | 5.1667  | 3100 | 1.0231          | 0.8363   | 0.8703    | 0.8363 | 0.8312 |
| 0.0239        | 5.3333  | 3200 | 0.7746          | 0.8683   | 0.8767    | 0.8683 | 0.8690 |
| 0.0087        | 5.5     | 3300 | 0.8246          | 0.8567   | 0.8700    | 0.8567 | 0.8561 |
| 0.001         | 5.6667  | 3400 | 1.0921          | 0.8237   | 0.8484    | 0.8237 | 0.8208 |
| 0.0056        | 5.8333  | 3500 | 0.7431          | 0.8533   | 0.8562    | 0.8533 | 0.8524 |
| 0.0007        | 6.0     | 3600 | 0.8992          | 0.8213   | 0.8463    | 0.8213 | 0.8270 |
| 0.0041        | 6.1667  | 3700 | 0.8531          | 0.8438   | 0.8757    | 0.8438 | 0.8454 |
| 0.0138        | 6.3333  | 3800 | 0.6643          | 0.8821   | 0.8918    | 0.8821 | 0.8809 |
| 0.0005        | 6.5     | 3900 | 0.6779          | 0.8862   | 0.8970    | 0.8862 | 0.8877 |
| 0.0005        | 6.6667  | 4000 | 0.7109          | 0.8892   | 0.9030    | 0.8892 | 0.8903 |
| 0.0005        | 6.8333  | 4100 | 0.7191          | 0.8908   | 0.9013    | 0.8908 | 0.8911 |
| 0.0006        | 7.0     | 4200 | 0.8573          | 0.8675   | 0.8846    | 0.8675 | 0.8635 |
| 0.064         | 7.1667  | 4300 | 0.9180          | 0.8608   | 0.8743    | 0.8608 | 0.8603 |
| 0.0005        | 7.3333  | 4400 | 0.7651          | 0.8767   | 0.8885    | 0.8767 | 0.8763 |
| 0.0007        | 7.5     | 4500 | 0.8158          | 0.8571   | 0.8703    | 0.8571 | 0.8569 |
| 0.0004        | 7.6667  | 4600 | 0.8329          | 0.8504   | 0.8709    | 0.8504 | 0.8517 |
| 0.0003        | 7.8333  | 4700 | 0.9078          | 0.8454   | 0.8605    | 0.8454 | 0.8446 |
| 0.0003        | 8.0     | 4800 | 0.8859          | 0.8529   | 0.8684    | 0.8529 | 0.8538 |
| 0.0003        | 8.1667  | 4900 | 0.9303          | 0.8479   | 0.8669    | 0.8479 | 0.8491 |
| 0.0002        | 8.3333  | 5000 | 0.9324          | 0.8475   | 0.8676    | 0.8475 | 0.8483 |
| 0.0002        | 8.5     | 5100 | 0.9206          | 0.8533   | 0.8733    | 0.8533 | 0.8544 |
| 0.0002        | 8.6667  | 5200 | 0.8745          | 0.8621   | 0.8813    | 0.8621 | 0.8630 |
| 0.0002        | 8.8333  | 5300 | 0.9208          | 0.8567   | 0.8764    | 0.8567 | 0.8575 |
| 0.0002        | 9.0     | 5400 | 0.9221          | 0.8583   | 0.8776    | 0.8583 | 0.8592 |
| 0.0002        | 9.1667  | 5500 | 0.9255          | 0.8588   | 0.8777    | 0.8588 | 0.8596 |
| 0.0002        | 9.3333  | 5600 | 0.9285          | 0.8583   | 0.8772    | 0.8583 | 0.8592 |
| 0.0001        | 9.5     | 5700 | 0.9288          | 0.8592   | 0.8780    | 0.8592 | 0.8601 |
| 0.0001        | 9.6667  | 5800 | 0.9305          | 0.8596   | 0.8782    | 0.8596 | 0.8605 |
| 0.0002        | 9.8333  | 5900 | 0.9323          | 0.8596   | 0.8782    | 0.8596 | 0.8605 |
| 0.0001        | 10.0    | 6000 | 0.9335          | 0.8596   | 0.8782    | 0.8596 | 0.8606 |
| 0.0001        | 10.1667 | 6100 | 0.9336          | 0.8608   | 0.8791    | 0.8608 | 0.8619 |
| 0.0001        | 10.3333 | 6200 | 0.9360          | 0.8612   | 0.8795    | 0.8612 | 0.8623 |
| 0.0001        | 10.5    | 6300 | 0.9374          | 0.8625   | 0.8803    | 0.8625 | 0.8635 |
| 0.0001        | 10.6667 | 6400 | 0.9406          | 0.8629   | 0.8809    | 0.8629 | 0.8640 |
| 0.0001        | 10.8333 | 6500 | 0.9420          | 0.8633   | 0.8810    | 0.8633 | 0.8643 |
| 0.0001        | 11.0    | 6600 | 0.9443          | 0.8633   | 0.8810    | 0.8633 | 0.8643 |
| 0.0001        | 11.1667 | 6700 | 0.9452          | 0.8633   | 0.8810    | 0.8633 | 0.8643 |
| 0.0001        | 11.3333 | 6800 | 0.9476          | 0.8638   | 0.8813    | 0.8638 | 0.8647 |
| 0.0001        | 11.5    | 6900 | 0.9495          | 0.8638   | 0.8813    | 0.8638 | 0.8647 |
| 0.0001        | 11.6667 | 7000 | 0.9501          | 0.8642   | 0.8818    | 0.8642 | 0.8652 |
| 0.0001        | 11.8333 | 7100 | 0.9528          | 0.8646   | 0.8820    | 0.8646 | 0.8656 |
| 0.0001        | 12.0    | 7200 | 0.9547          | 0.8646   | 0.8820    | 0.8646 | 0.8656 |
| 0.0001        | 12.1667 | 7300 | 0.9574          | 0.8646   | 0.8820    | 0.8646 | 0.8656 |
| 0.0001        | 12.3333 | 7400 | 0.9586          | 0.8646   | 0.8820    | 0.8646 | 0.8656 |
| 0.0001        | 12.5    | 7500 | 0.9594          | 0.8646   | 0.8820    | 0.8646 | 0.8656 |
| 0.0001        | 12.6667 | 7600 | 0.9611          | 0.8646   | 0.8820    | 0.8646 | 0.8656 |
| 0.0001        | 12.8333 | 7700 | 0.9627          | 0.8646   | 0.8820    | 0.8646 | 0.8656 |
| 0.0001        | 13.0    | 7800 | 0.9639          | 0.8646   | 0.8820    | 0.8646 | 0.8656 |
| 0.0001        | 13.1667 | 7900 | 0.9656          | 0.8646   | 0.8820    | 0.8646 | 0.8656 |
| 0.0001        | 13.3333 | 8000 | 0.9662          | 0.8646   | 0.8820    | 0.8646 | 0.8655 |
| 0.0001        | 13.5    | 8100 | 0.9675          | 0.8642   | 0.8815    | 0.8642 | 0.8651 |
| 0.0001        | 13.6667 | 8200 | 0.9684          | 0.8642   | 0.8814    | 0.8642 | 0.8651 |
| 0.0001        | 13.8333 | 8300 | 0.9695          | 0.8646   | 0.8818    | 0.8646 | 0.8656 |
| 0.0001        | 14.0    | 8400 | 0.9706          | 0.8646   | 0.8818    | 0.8646 | 0.8656 |
| 0.0001        | 14.1667 | 8500 | 0.9714          | 0.8646   | 0.8818    | 0.8646 | 0.8656 |
| 0.0001        | 14.3333 | 8600 | 0.9724          | 0.8646   | 0.8818    | 0.8646 | 0.8656 |
| 0.0001        | 14.5    | 8700 | 0.9727          | 0.8646   | 0.8818    | 0.8646 | 0.8656 |
| 0.0001        | 14.6667 | 8800 | 0.9733          | 0.8646   | 0.8818    | 0.8646 | 0.8656 |
| 0.0001        | 14.8333 | 8900 | 0.9734          | 0.8646   | 0.8818    | 0.8646 | 0.8656 |
| 0.0001        | 15.0    | 9000 | 0.9736          | 0.8646   | 0.8818    | 0.8646 | 0.8656 |


### 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