
<!-- 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-patch16-224-75-fold3

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: 0.2177
- Accuracy: 0.9535

## 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    | 0.5697          | 0.6744   |
| No log        | 2.0   | 4    | 0.6348          | 0.6977   |
| No log        | 3.0   | 6    | 0.8030          | 0.6977   |
| No log        | 4.0   | 8    | 0.7092          | 0.6977   |
| 0.5313        | 5.0   | 10   | 0.4644          | 0.8140   |
| 0.5313        | 6.0   | 12   | 0.4211          | 0.7907   |
| 0.5313        | 7.0   | 14   | 0.4913          | 0.8140   |
| 0.5313        | 8.0   | 16   | 0.4788          | 0.8372   |
| 0.5313        | 9.0   | 18   | 0.3717          | 0.7907   |
| 0.3672        | 10.0  | 20   | 0.3763          | 0.8140   |
| 0.3672        | 11.0  | 22   | 0.5082          | 0.8372   |
| 0.3672        | 12.0  | 24   | 0.3661          | 0.8140   |
| 0.3672        | 13.0  | 26   | 0.3693          | 0.8140   |
| 0.3672        | 14.0  | 28   | 0.3808          | 0.8605   |
| 0.2837        | 15.0  | 30   | 0.3492          | 0.8372   |
| 0.2837        | 16.0  | 32   | 0.3446          | 0.7907   |
| 0.2837        | 17.0  | 34   | 0.3909          | 0.8605   |
| 0.2837        | 18.0  | 36   | 0.4379          | 0.8372   |
| 0.2837        | 19.0  | 38   | 0.3905          | 0.8140   |
| 0.2268        | 20.0  | 40   | 0.3453          | 0.8140   |
| 0.2268        | 21.0  | 42   | 0.4145          | 0.8372   |
| 0.2268        | 22.0  | 44   | 0.3370          | 0.8372   |
| 0.2268        | 23.0  | 46   | 0.3502          | 0.8372   |
| 0.2268        | 24.0  | 48   | 0.3295          | 0.8372   |
| 0.1735        | 25.0  | 50   | 0.3118          | 0.8837   |
| 0.1735        | 26.0  | 52   | 0.3050          | 0.8837   |
| 0.1735        | 27.0  | 54   | 0.6940          | 0.8140   |
| 0.1735        | 28.0  | 56   | 0.5913          | 0.8372   |
| 0.1735        | 29.0  | 58   | 0.3190          | 0.8837   |
| 0.1221        | 30.0  | 60   | 0.4141          | 0.8372   |
| 0.1221        | 31.0  | 62   | 0.4572          | 0.8372   |
| 0.1221        | 32.0  | 64   | 0.3048          | 0.8837   |
| 0.1221        | 33.0  | 66   | 0.3139          | 0.9070   |
| 0.1221        | 34.0  | 68   | 0.3090          | 0.8837   |
| 0.1158        | 35.0  | 70   | 0.3393          | 0.8837   |
| 0.1158        | 36.0  | 72   | 0.3035          | 0.8605   |
| 0.1158        | 37.0  | 74   | 0.4730          | 0.8140   |
| 0.1158        | 38.0  | 76   | 0.3788          | 0.8605   |
| 0.1158        | 39.0  | 78   | 0.2904          | 0.8837   |
| 0.1075        | 40.0  | 80   | 0.2750          | 0.8837   |
| 0.1075        | 41.0  | 82   | 0.3328          | 0.8837   |
| 0.1075        | 42.0  | 84   | 0.2648          | 0.9070   |
| 0.1075        | 43.0  | 86   | 0.2517          | 0.8837   |
| 0.1075        | 44.0  | 88   | 0.4402          | 0.8837   |
| 0.0925        | 45.0  | 90   | 0.4076          | 0.8837   |
| 0.0925        | 46.0  | 92   | 0.2390          | 0.9070   |
| 0.0925        | 47.0  | 94   | 0.2176          | 0.9070   |
| 0.0925        | 48.0  | 96   | 0.2580          | 0.9302   |
| 0.0925        | 49.0  | 98   | 0.2049          | 0.9070   |
| 0.1085        | 50.0  | 100  | 0.2244          | 0.8837   |
| 0.1085        | 51.0  | 102  | 0.2377          | 0.9070   |
| 0.1085        | 52.0  | 104  | 0.4591          | 0.8372   |
| 0.1085        | 53.0  | 106  | 0.5054          | 0.8372   |
| 0.1085        | 54.0  | 108  | 0.2994          | 0.9302   |
| 0.0876        | 55.0  | 110  | 0.2387          | 0.9070   |
| 0.0876        | 56.0  | 112  | 0.3078          | 0.9070   |
| 0.0876        | 57.0  | 114  | 0.4470          | 0.8372   |
| 0.0876        | 58.0  | 116  | 0.3457          | 0.9070   |
| 0.0876        | 59.0  | 118  | 0.2655          | 0.9070   |
| 0.0823        | 60.0  | 120  | 0.2150          | 0.9070   |
| 0.0823        | 61.0  | 122  | 0.2116          | 0.9070   |
| 0.0823        | 62.0  | 124  | 0.2305          | 0.9302   |
| 0.0823        | 63.0  | 126  | 0.2070          | 0.9302   |
| 0.0823        | 64.0  | 128  | 0.1808          | 0.9070   |
| 0.0791        | 65.0  | 130  | 0.1669          | 0.9070   |
| 0.0791        | 66.0  | 132  | 0.1721          | 0.9070   |
| 0.0791        | 67.0  | 134  | 0.2194          | 0.9302   |
| 0.0791        | 68.0  | 136  | 0.3454          | 0.8837   |
| 0.0791        | 69.0  | 138  | 0.5415          | 0.8372   |
| 0.0607        | 70.0  | 140  | 0.4457          | 0.8605   |
| 0.0607        | 71.0  | 142  | 0.2411          | 0.8837   |
| 0.0607        | 72.0  | 144  | 0.2057          | 0.9070   |
| 0.0607        | 73.0  | 146  | 0.2200          | 0.9070   |
| 0.0607        | 74.0  | 148  | 0.2677          | 0.8837   |
| 0.0715        | 75.0  | 150  | 0.2950          | 0.8837   |
| 0.0715        | 76.0  | 152  | 0.2874          | 0.8837   |
| 0.0715        | 77.0  | 154  | 0.2236          | 0.9070   |
| 0.0715        | 78.0  | 156  | 0.2052          | 0.9302   |
| 0.0715        | 79.0  | 158  | 0.2177          | 0.9535   |
| 0.0644        | 80.0  | 160  | 0.2178          | 0.9535   |
| 0.0644        | 81.0  | 162  | 0.2126          | 0.9302   |
| 0.0644        | 82.0  | 164  | 0.2127          | 0.9302   |
| 0.0644        | 83.0  | 166  | 0.2216          | 0.9070   |
| 0.0644        | 84.0  | 168  | 0.2420          | 0.9070   |
| 0.0622        | 85.0  | 170  | 0.2305          | 0.9070   |
| 0.0622        | 86.0  | 172  | 0.2247          | 0.9070   |
| 0.0622        | 87.0  | 174  | 0.2492          | 0.9070   |
| 0.0622        | 88.0  | 176  | 0.3292          | 0.8837   |
| 0.0622        | 89.0  | 178  | 0.3876          | 0.8837   |
| 0.0564        | 90.0  | 180  | 0.3886          | 0.8837   |
| 0.0564        | 91.0  | 182  | 0.3707          | 0.8837   |
| 0.0564        | 92.0  | 184  | 0.3377          | 0.8837   |
| 0.0564        | 93.0  | 186  | 0.3186          | 0.8837   |
| 0.0564        | 94.0  | 188  | 0.3038          | 0.8837   |
| 0.0578        | 95.0  | 190  | 0.2818          | 0.8605   |
| 0.0578        | 96.0  | 192  | 0.2756          | 0.8837   |
| 0.0578        | 97.0  | 194  | 0.2694          | 0.8837   |
| 0.0578        | 98.0  | 196  | 0.2698          | 0.8837   |
| 0.0578        | 99.0  | 198  | 0.2732          | 0.8837   |
| 0.0424        | 100.0 | 200  | 0.2739          | 0.8837   |


### Framework versions

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

hasta normal