
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# deit-base-distilled-patch16-224-85-fold4

This model is a fine-tuned version of [facebook/deit-base-distilled-patch16-224](https://huggingface.co/facebook/deit-base-distilled-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2141
- Accuracy: 0.9318

## 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: 5e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 100

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 2    | 0.6100          | 0.7273   |
| No log        | 2.0   | 4    | 0.6938          | 0.7045   |
| No log        | 3.0   | 6    | 0.7568          | 0.7045   |
| No log        | 4.0   | 8    | 0.6140          | 0.7045   |
| 0.5388        | 5.0   | 10   | 0.4976          | 0.75     |
| 0.5388        | 6.0   | 12   | 0.4809          | 0.7273   |
| 0.5388        | 7.0   | 14   | 0.5276          | 0.7273   |
| 0.5388        | 8.0   | 16   | 0.4455          | 0.7955   |
| 0.5388        | 9.0   | 18   | 0.3915          | 0.8409   |
| 0.4154        | 10.0  | 20   | 0.5070          | 0.7955   |
| 0.4154        | 11.0  | 22   | 0.3747          | 0.8182   |
| 0.4154        | 12.0  | 24   | 0.3027          | 0.8864   |
| 0.4154        | 13.0  | 26   | 0.3053          | 0.8636   |
| 0.4154        | 14.0  | 28   | 0.3194          | 0.8409   |
| 0.3258        | 15.0  | 30   | 0.3134          | 0.8864   |
| 0.3258        | 16.0  | 32   | 0.2925          | 0.8864   |
| 0.3258        | 17.0  | 34   | 0.2449          | 0.8864   |
| 0.3258        | 18.0  | 36   | 0.2308          | 0.8864   |
| 0.3258        | 19.0  | 38   | 0.2141          | 0.9318   |
| 0.2528        | 20.0  | 40   | 0.2330          | 0.9318   |
| 0.2528        | 21.0  | 42   | 0.2173          | 0.9318   |
| 0.2528        | 22.0  | 44   | 0.2450          | 0.9091   |
| 0.2528        | 23.0  | 46   | 0.2549          | 0.9091   |
| 0.2528        | 24.0  | 48   | 0.4341          | 0.75     |
| 0.175         | 25.0  | 50   | 0.2358          | 0.9091   |
| 0.175         | 26.0  | 52   | 0.2828          | 0.8864   |
| 0.175         | 27.0  | 54   | 0.2236          | 0.9091   |
| 0.175         | 28.0  | 56   | 0.2591          | 0.8636   |
| 0.175         | 29.0  | 58   | 0.2702          | 0.8864   |
| 0.169         | 30.0  | 60   | 0.2910          | 0.8636   |
| 0.169         | 31.0  | 62   | 0.3594          | 0.9091   |
| 0.169         | 32.0  | 64   | 0.4246          | 0.8864   |
| 0.169         | 33.0  | 66   | 0.2655          | 0.8864   |
| 0.169         | 34.0  | 68   | 0.2581          | 0.8864   |
| 0.1336        | 35.0  | 70   | 0.2494          | 0.8409   |
| 0.1336        | 36.0  | 72   | 0.2438          | 0.8636   |
| 0.1336        | 37.0  | 74   | 0.3246          | 0.8636   |
| 0.1336        | 38.0  | 76   | 0.2887          | 0.8409   |
| 0.1336        | 39.0  | 78   | 0.3559          | 0.8409   |
| 0.1281        | 40.0  | 80   | 0.3274          | 0.8864   |
| 0.1281        | 41.0  | 82   | 0.3371          | 0.8409   |
| 0.1281        | 42.0  | 84   | 0.3902          | 0.8409   |
| 0.1281        | 43.0  | 86   | 0.3100          | 0.8409   |
| 0.1281        | 44.0  | 88   | 0.3113          | 0.8636   |
| 0.136         | 45.0  | 90   | 0.3244          | 0.8409   |
| 0.136         | 46.0  | 92   | 0.3765          | 0.8864   |
| 0.136         | 47.0  | 94   | 0.3838          | 0.8864   |
| 0.136         | 48.0  | 96   | 0.3845          | 0.7955   |
| 0.136         | 49.0  | 98   | 0.3910          | 0.7955   |
| 0.0934        | 50.0  | 100  | 0.4889          | 0.8636   |
| 0.0934        | 51.0  | 102  | 0.6680          | 0.8182   |
| 0.0934        | 52.0  | 104  | 0.4264          | 0.8864   |
| 0.0934        | 53.0  | 106  | 0.3266          | 0.8182   |
| 0.0934        | 54.0  | 108  | 0.3168          | 0.8864   |
| 0.0999        | 55.0  | 110  | 0.3671          | 0.8182   |
| 0.0999        | 56.0  | 112  | 0.4684          | 0.8182   |
| 0.0999        | 57.0  | 114  | 0.4254          | 0.8182   |
| 0.0999        | 58.0  | 116  | 0.3195          | 0.8182   |
| 0.0999        | 59.0  | 118  | 0.3860          | 0.8864   |
| 0.1145        | 60.0  | 120  | 0.4805          | 0.8636   |
| 0.1145        | 61.0  | 122  | 0.3864          | 0.8182   |
| 0.1145        | 62.0  | 124  | 0.3347          | 0.8182   |
| 0.1145        | 63.0  | 126  | 0.3144          | 0.8182   |
| 0.1145        | 64.0  | 128  | 0.3267          | 0.8636   |
| 0.0769        | 65.0  | 130  | 0.3592          | 0.8636   |
| 0.0769        | 66.0  | 132  | 0.3520          | 0.8636   |
| 0.0769        | 67.0  | 134  | 0.3632          | 0.8636   |
| 0.0769        | 68.0  | 136  | 0.3955          | 0.8636   |
| 0.0769        | 69.0  | 138  | 0.4053          | 0.8182   |
| 0.0976        | 70.0  | 140  | 0.4272          | 0.8636   |
| 0.0976        | 71.0  | 142  | 0.4345          | 0.8409   |
| 0.0976        | 72.0  | 144  | 0.3943          | 0.8636   |
| 0.0976        | 73.0  | 146  | 0.3827          | 0.8636   |
| 0.0976        | 74.0  | 148  | 0.4133          | 0.8409   |
| 0.0981        | 75.0  | 150  | 0.4311          | 0.8409   |
| 0.0981        | 76.0  | 152  | 0.4126          | 0.8409   |
| 0.0981        | 77.0  | 154  | 0.3651          | 0.8636   |
| 0.0981        | 78.0  | 156  | 0.3511          | 0.8182   |
| 0.0981        | 79.0  | 158  | 0.3625          | 0.8636   |
| 0.085         | 80.0  | 160  | 0.3607          | 0.8636   |
| 0.085         | 81.0  | 162  | 0.3470          | 0.8409   |
| 0.085         | 82.0  | 164  | 0.3639          | 0.8409   |
| 0.085         | 83.0  | 166  | 0.3750          | 0.8409   |
| 0.085         | 84.0  | 168  | 0.3726          | 0.7955   |
| 0.0831        | 85.0  | 170  | 0.3740          | 0.8182   |
| 0.0831        | 86.0  | 172  | 0.3807          | 0.8636   |
| 0.0831        | 87.0  | 174  | 0.3875          | 0.8636   |
| 0.0831        | 88.0  | 176  | 0.3886          | 0.8409   |
| 0.0831        | 89.0  | 178  | 0.4017          | 0.7955   |
| 0.0811        | 90.0  | 180  | 0.4271          | 0.7955   |
| 0.0811        | 91.0  | 182  | 0.4293          | 0.7955   |
| 0.0811        | 92.0  | 184  | 0.4243          | 0.7727   |
| 0.0811        | 93.0  | 186  | 0.4088          | 0.7727   |
| 0.0811        | 94.0  | 188  | 0.3986          | 0.7955   |
| 0.0692        | 95.0  | 190  | 0.3963          | 0.8182   |
| 0.0692        | 96.0  | 192  | 0.3987          | 0.8636   |
| 0.0692        | 97.0  | 194  | 0.4020          | 0.8636   |
| 0.0692        | 98.0  | 196  | 0.4015          | 0.8636   |
| 0.0692        | 99.0  | 198  | 0.4009          | 0.8636   |
| 0.0644        | 100.0 | 200  | 0.4002          | 0.8636   |


### Framework versions

- Transformers 4.41.0
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1

hasta normal