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# beit-base-patch16-224-85-fold4

This model is a fine-tuned version of [microsoft/beit-base-patch16-224](https://huggingface.co/microsoft/beit-base-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1725
- Accuracy: 0.9545

## 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    | 0.6874          | 0.6818   |
| No log        | 2.0   | 4    | 0.7083          | 0.7045   |
| No log        | 3.0   | 6    | 0.8871          | 0.7045   |
| No log        | 4.0   | 8    | 0.7305          | 0.7045   |
| 0.6246        | 5.0   | 10   | 0.5791          | 0.7045   |
| 0.6246        | 6.0   | 12   | 0.5888          | 0.7045   |
| 0.6246        | 7.0   | 14   | 0.6050          | 0.7045   |
| 0.6246        | 8.0   | 16   | 0.5468          | 0.7045   |
| 0.6246        | 9.0   | 18   | 0.5351          | 0.7045   |
| 0.4453        | 10.0  | 20   | 0.4155          | 0.8409   |
| 0.4453        | 11.0  | 22   | 0.8266          | 0.7045   |
| 0.4453        | 12.0  | 24   | 0.3905          | 0.8409   |
| 0.4453        | 13.0  | 26   | 0.3942          | 0.8409   |
| 0.4453        | 14.0  | 28   | 0.4015          | 0.8409   |
| 0.3613        | 15.0  | 30   | 0.3474          | 0.8182   |
| 0.3613        | 16.0  | 32   | 0.4763          | 0.8182   |
| 0.3613        | 17.0  | 34   | 0.3894          | 0.7955   |
| 0.3613        | 18.0  | 36   | 0.4290          | 0.7955   |
| 0.3613        | 19.0  | 38   | 0.3525          | 0.8636   |
| 0.2928        | 20.0  | 40   | 0.3426          | 0.8864   |
| 0.2928        | 21.0  | 42   | 0.4060          | 0.8182   |
| 0.2928        | 22.0  | 44   | 0.6962          | 0.75     |
| 0.2928        | 23.0  | 46   | 0.3514          | 0.8636   |
| 0.2928        | 24.0  | 48   | 0.5302          | 0.8409   |
| 0.2256        | 25.0  | 50   | 0.3094          | 0.8636   |
| 0.2256        | 26.0  | 52   | 0.2977          | 0.8636   |
| 0.2256        | 27.0  | 54   | 0.4883          | 0.8182   |
| 0.2256        | 28.0  | 56   | 0.3008          | 0.8409   |
| 0.2256        | 29.0  | 58   | 0.3226          | 0.8409   |
| 0.2231        | 30.0  | 60   | 0.4101          | 0.8409   |
| 0.2231        | 31.0  | 62   | 0.3197          | 0.8409   |
| 0.2231        | 32.0  | 64   | 0.4133          | 0.7727   |
| 0.2231        | 33.0  | 66   | 0.2923          | 0.8636   |
| 0.2231        | 34.0  | 68   | 0.4391          | 0.8636   |
| 0.1756        | 35.0  | 70   | 0.3016          | 0.8636   |
| 0.1756        | 36.0  | 72   | 0.2749          | 0.9091   |
| 0.1756        | 37.0  | 74   | 0.3146          | 0.8864   |
| 0.1756        | 38.0  | 76   | 0.3095          | 0.8409   |
| 0.1756        | 39.0  | 78   | 0.3017          | 0.8864   |
| 0.1592        | 40.0  | 80   | 0.2762          | 0.8864   |
| 0.1592        | 41.0  | 82   | 0.4054          | 0.8409   |
| 0.1592        | 42.0  | 84   | 0.2787          | 0.8864   |
| 0.1592        | 43.0  | 86   | 0.3193          | 0.8636   |
| 0.1592        | 44.0  | 88   | 0.2783          | 0.9091   |
| 0.1857        | 45.0  | 90   | 0.2934          | 0.9091   |
| 0.1857        | 46.0  | 92   | 0.3579          | 0.8636   |
| 0.1857        | 47.0  | 94   | 0.3501          | 0.8864   |
| 0.1857        | 48.0  | 96   | 0.3358          | 0.8864   |
| 0.1857        | 49.0  | 98   | 0.2981          | 0.9091   |
| 0.1179        | 50.0  | 100  | 0.3364          | 0.8636   |
| 0.1179        | 51.0  | 102  | 0.3324          | 0.8636   |
| 0.1179        | 52.0  | 104  | 0.1725          | 0.9545   |
| 0.1179        | 53.0  | 106  | 0.1222          | 0.9545   |
| 0.1179        | 54.0  | 108  | 0.1500          | 0.9091   |
| 0.1448        | 55.0  | 110  | 0.2358          | 0.9091   |
| 0.1448        | 56.0  | 112  | 0.2224          | 0.9091   |
| 0.1448        | 57.0  | 114  | 0.1457          | 0.9318   |
| 0.1448        | 58.0  | 116  | 0.1745          | 0.9318   |
| 0.1448        | 59.0  | 118  | 0.1990          | 0.9091   |
| 0.1343        | 60.0  | 120  | 0.2905          | 0.8864   |
| 0.1343        | 61.0  | 122  | 0.3842          | 0.8864   |
| 0.1343        | 62.0  | 124  | 0.3031          | 0.8864   |
| 0.1343        | 63.0  | 126  | 0.2642          | 0.8864   |
| 0.1343        | 64.0  | 128  | 0.2412          | 0.9091   |
| 0.1109        | 65.0  | 130  | 0.3347          | 0.8864   |
| 0.1109        | 66.0  | 132  | 0.4005          | 0.8864   |
| 0.1109        | 67.0  | 134  | 0.2905          | 0.8864   |
| 0.1109        | 68.0  | 136  | 0.3168          | 0.9318   |
| 0.1109        | 69.0  | 138  | 0.3845          | 0.8864   |
| 0.1221        | 70.0  | 140  | 0.3178          | 0.9318   |
| 0.1221        | 71.0  | 142  | 0.2690          | 0.9318   |
| 0.1221        | 72.0  | 144  | 0.2516          | 0.8864   |
| 0.1221        | 73.0  | 146  | 0.2347          | 0.9091   |
| 0.1221        | 74.0  | 148  | 0.2376          | 0.9318   |
| 0.1191        | 75.0  | 150  | 0.2480          | 0.9318   |
| 0.1191        | 76.0  | 152  | 0.2597          | 0.9091   |
| 0.1191        | 77.0  | 154  | 0.3071          | 0.9091   |
| 0.1191        | 78.0  | 156  | 0.3354          | 0.9091   |
| 0.1191        | 79.0  | 158  | 0.2988          | 0.8864   |
| 0.1133        | 80.0  | 160  | 0.2760          | 0.9091   |
| 0.1133        | 81.0  | 162  | 0.2832          | 0.9318   |
| 0.1133        | 82.0  | 164  | 0.2793          | 0.9318   |
| 0.1133        | 83.0  | 166  | 0.2779          | 0.9091   |
| 0.1133        | 84.0  | 168  | 0.3004          | 0.8864   |
| 0.098         | 85.0  | 170  | 0.3275          | 0.8864   |
| 0.098         | 86.0  | 172  | 0.3394          | 0.8864   |
| 0.098         | 87.0  | 174  | 0.3257          | 0.8864   |
| 0.098         | 88.0  | 176  | 0.3172          | 0.8864   |
| 0.098         | 89.0  | 178  | 0.3122          | 0.9318   |
| 0.0917        | 90.0  | 180  | 0.3208          | 0.9318   |
| 0.0917        | 91.0  | 182  | 0.3236          | 0.9318   |
| 0.0917        | 92.0  | 184  | 0.3274          | 0.9318   |
| 0.0917        | 93.0  | 186  | 0.3331          | 0.8864   |
| 0.0917        | 94.0  | 188  | 0.3379          | 0.8864   |
| 0.0989        | 95.0  | 190  | 0.3404          | 0.8864   |
| 0.0989        | 96.0  | 192  | 0.3452          | 0.8864   |
| 0.0989        | 97.0  | 194  | 0.3491          | 0.8864   |
| 0.0989        | 98.0  | 196  | 0.3489          | 0.8864   |
| 0.0989        | 99.0  | 198  | 0.3482          | 0.8864   |
| 0.0916        | 100.0 | 200  | 0.3467          | 0.8864   |


### Framework versions

- Transformers 4.40.2
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1

hasta normal