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# beit-base-patch16-224-85-fold5

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: 0.2499
- 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    | 1.0896          | 0.2955   |
| No log        | 2.0   | 4    | 0.6456          | 0.7273   |
| No log        | 3.0   | 6    | 1.0355          | 0.7045   |
| No log        | 4.0   | 8    | 0.9124          | 0.7045   |
| 0.7607        | 5.0   | 10   | 0.5809          | 0.7955   |
| 0.7607        | 6.0   | 12   | 0.6812          | 0.75     |
| 0.7607        | 7.0   | 14   | 0.6529          | 0.75     |
| 0.7607        | 8.0   | 16   | 0.7174          | 0.7273   |
| 0.7607        | 9.0   | 18   | 0.6619          | 0.6136   |
| 0.4221        | 10.0  | 20   | 0.8063          | 0.75     |
| 0.4221        | 11.0  | 22   | 0.6372          | 0.75     |
| 0.4221        | 12.0  | 24   | 0.5886          | 0.75     |
| 0.4221        | 13.0  | 26   | 0.6359          | 0.6364   |
| 0.4221        | 14.0  | 28   | 0.5585          | 0.75     |
| 0.3287        | 15.0  | 30   | 0.4541          | 0.7273   |
| 0.3287        | 16.0  | 32   | 0.7624          | 0.5682   |
| 0.3287        | 17.0  | 34   | 0.6806          | 0.75     |
| 0.3287        | 18.0  | 36   | 0.7708          | 0.7273   |
| 0.3287        | 19.0  | 38   | 0.4170          | 0.7273   |
| 0.3663        | 20.0  | 40   | 0.4282          | 0.7727   |
| 0.3663        | 21.0  | 42   | 0.5613          | 0.75     |
| 0.3663        | 22.0  | 44   | 0.4025          | 0.8409   |
| 0.3663        | 23.0  | 46   | 0.4109          | 0.7955   |
| 0.3663        | 24.0  | 48   | 0.4373          | 0.8409   |
| 0.2344        | 25.0  | 50   | 0.3211          | 0.8864   |
| 0.2344        | 26.0  | 52   | 0.5561          | 0.75     |
| 0.2344        | 27.0  | 54   | 0.3149          | 0.8636   |
| 0.2344        | 28.0  | 56   | 0.3166          | 0.7955   |
| 0.2344        | 29.0  | 58   | 0.4164          | 0.8636   |
| 0.2051        | 30.0  | 60   | 0.4345          | 0.8636   |
| 0.2051        | 31.0  | 62   | 0.3180          | 0.8636   |
| 0.2051        | 32.0  | 64   | 0.3673          | 0.8409   |
| 0.2051        | 33.0  | 66   | 0.4313          | 0.8409   |
| 0.2051        | 34.0  | 68   | 0.4359          | 0.8409   |
| 0.1694        | 35.0  | 70   | 0.3700          | 0.8182   |
| 0.1694        | 36.0  | 72   | 0.5843          | 0.7955   |
| 0.1694        | 37.0  | 74   | 0.4064          | 0.8636   |
| 0.1694        | 38.0  | 76   | 0.3992          | 0.8182   |
| 0.1694        | 39.0  | 78   | 0.3153          | 0.8636   |
| 0.1566        | 40.0  | 80   | 0.5581          | 0.8182   |
| 0.1566        | 41.0  | 82   | 0.2921          | 0.8636   |
| 0.1566        | 42.0  | 84   | 0.3217          | 0.8864   |
| 0.1566        | 43.0  | 86   | 0.3255          | 0.8864   |
| 0.1566        | 44.0  | 88   | 0.7238          | 0.75     |
| 0.1389        | 45.0  | 90   | 0.4053          | 0.8864   |
| 0.1389        | 46.0  | 92   | 0.2499          | 0.9318   |
| 0.1389        | 47.0  | 94   | 0.2584          | 0.8864   |
| 0.1389        | 48.0  | 96   | 0.4432          | 0.8409   |
| 0.1389        | 49.0  | 98   | 0.6965          | 0.7955   |
| 0.1311        | 50.0  | 100  | 0.3910          | 0.8409   |
| 0.1311        | 51.0  | 102  | 0.3017          | 0.8636   |
| 0.1311        | 52.0  | 104  | 0.3050          | 0.8636   |
| 0.1311        | 53.0  | 106  | 0.2193          | 0.8636   |
| 0.1311        | 54.0  | 108  | 0.2369          | 0.8409   |
| 0.1386        | 55.0  | 110  | 0.3143          | 0.8864   |
| 0.1386        | 56.0  | 112  | 0.2932          | 0.8864   |
| 0.1386        | 57.0  | 114  | 0.2725          | 0.9091   |
| 0.1386        | 58.0  | 116  | 0.5664          | 0.8409   |
| 0.1386        | 59.0  | 118  | 0.5875          | 0.8182   |
| 0.1194        | 60.0  | 120  | 0.4623          | 0.8636   |
| 0.1194        | 61.0  | 122  | 0.4716          | 0.8182   |
| 0.1194        | 62.0  | 124  | 0.5028          | 0.8182   |
| 0.1194        | 63.0  | 126  | 0.4558          | 0.8182   |
| 0.1194        | 64.0  | 128  | 0.4798          | 0.8182   |
| 0.1122        | 65.0  | 130  | 0.3827          | 0.8409   |
| 0.1122        | 66.0  | 132  | 0.3653          | 0.8409   |
| 0.1122        | 67.0  | 134  | 0.3972          | 0.8409   |
| 0.1122        | 68.0  | 136  | 0.5705          | 0.7727   |
| 0.1122        | 69.0  | 138  | 0.5935          | 0.7727   |
| 0.1041        | 70.0  | 140  | 0.3905          | 0.8636   |
| 0.1041        | 71.0  | 142  | 0.2791          | 0.8409   |
| 0.1041        | 72.0  | 144  | 0.2845          | 0.9091   |
| 0.1041        | 73.0  | 146  | 0.2401          | 0.8636   |
| 0.1041        | 74.0  | 148  | 0.2260          | 0.8864   |
| 0.0982        | 75.0  | 150  | 0.2454          | 0.8864   |
| 0.0982        | 76.0  | 152  | 0.3773          | 0.8864   |
| 0.0982        | 77.0  | 154  | 0.6185          | 0.8182   |
| 0.0982        | 78.0  | 156  | 0.7238          | 0.7727   |
| 0.0982        | 79.0  | 158  | 0.5469          | 0.8409   |
| 0.1065        | 80.0  | 160  | 0.4318          | 0.8636   |
| 0.1065        | 81.0  | 162  | 0.3348          | 0.8864   |
| 0.1065        | 82.0  | 164  | 0.3041          | 0.8636   |
| 0.1065        | 83.0  | 166  | 0.3350          | 0.8864   |
| 0.1065        | 84.0  | 168  | 0.3464          | 0.8864   |
| 0.0829        | 85.0  | 170  | 0.3375          | 0.8864   |
| 0.0829        | 86.0  | 172  | 0.3309          | 0.8864   |
| 0.0829        | 87.0  | 174  | 0.3325          | 0.8864   |
| 0.0829        | 88.0  | 176  | 0.3441          | 0.8864   |
| 0.0829        | 89.0  | 178  | 0.3456          | 0.8636   |
| 0.0902        | 90.0  | 180  | 0.3244          | 0.8636   |
| 0.0902        | 91.0  | 182  | 0.3126          | 0.8636   |
| 0.0902        | 92.0  | 184  | 0.3117          | 0.8636   |
| 0.0902        | 93.0  | 186  | 0.2877          | 0.8636   |
| 0.0902        | 94.0  | 188  | 0.2643          | 0.8636   |
| 0.0838        | 95.0  | 190  | 0.2525          | 0.8864   |
| 0.0838        | 96.0  | 192  | 0.2462          | 0.9091   |
| 0.0838        | 97.0  | 194  | 0.2417          | 0.9091   |
| 0.0838        | 98.0  | 196  | 0.2402          | 0.9091   |
| 0.0838        | 99.0  | 198  | 0.2409          | 0.9091   |
| 0.0747        | 100.0 | 200  | 0.2426          | 0.9091   |


### Framework versions

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

hasta normal