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# beit-base-patch16-224-85-fold1

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: 0.1430
- Accuracy: 0.9773

## 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    | 0.7308          | 0.5455   |
| No log        | 2.0   | 4    | 0.7927          | 0.7045   |
| No log        | 3.0   | 6    | 0.9672          | 0.7045   |
| No log        | 4.0   | 8    | 0.6257          | 0.7045   |
| 0.6404        | 5.0   | 10   | 0.4646          | 0.7955   |
| 0.6404        | 6.0   | 12   | 0.5648          | 0.7045   |
| 0.6404        | 7.0   | 14   | 0.4389          | 0.7727   |
| 0.6404        | 8.0   | 16   | 0.4523          | 0.75     |
| 0.6404        | 9.0   | 18   | 0.4698          | 0.75     |
| 0.455         | 10.0  | 20   | 0.3707          | 0.8409   |
| 0.455         | 11.0  | 22   | 0.3594          | 0.8182   |
| 0.455         | 12.0  | 24   | 0.6136          | 0.7273   |
| 0.455         | 13.0  | 26   | 0.3022          | 0.8864   |
| 0.455         | 14.0  | 28   | 0.2919          | 0.8409   |
| 0.3981        | 15.0  | 30   | 0.3612          | 0.8182   |
| 0.3981        | 16.0  | 32   | 0.2492          | 0.8864   |
| 0.3981        | 17.0  | 34   | 0.2460          | 0.9091   |
| 0.3981        | 18.0  | 36   | 0.2931          | 0.8636   |
| 0.3981        | 19.0  | 38   | 0.1822          | 0.9091   |
| 0.3257        | 20.0  | 40   | 0.2060          | 0.9091   |
| 0.3257        | 21.0  | 42   | 0.2195          | 0.8864   |
| 0.3257        | 22.0  | 44   | 0.2624          | 0.9091   |
| 0.3257        | 23.0  | 46   | 0.2384          | 0.9091   |
| 0.3257        | 24.0  | 48   | 0.1767          | 0.9318   |
| 0.2553        | 25.0  | 50   | 0.2040          | 0.9318   |
| 0.2553        | 26.0  | 52   | 0.1981          | 0.9091   |
| 0.2553        | 27.0  | 54   | 0.1835          | 0.9318   |
| 0.2553        | 28.0  | 56   | 0.1820          | 0.9318   |
| 0.2553        | 29.0  | 58   | 0.1466          | 0.9545   |
| 0.2083        | 30.0  | 60   | 0.1668          | 0.9318   |
| 0.2083        | 31.0  | 62   | 0.2229          | 0.9318   |
| 0.2083        | 32.0  | 64   | 0.1783          | 0.9545   |
| 0.2083        | 33.0  | 66   | 0.1944          | 0.8864   |
| 0.2083        | 34.0  | 68   | 0.3025          | 0.9091   |
| 0.2353        | 35.0  | 70   | 0.4457          | 0.8409   |
| 0.2353        | 36.0  | 72   | 0.2759          | 0.9318   |
| 0.2353        | 37.0  | 74   | 0.2179          | 0.9318   |
| 0.2353        | 38.0  | 76   | 0.3911          | 0.9091   |
| 0.2353        | 39.0  | 78   | 0.5785          | 0.8409   |
| 0.1782        | 40.0  | 80   | 0.2339          | 0.9318   |
| 0.1782        | 41.0  | 82   | 0.2302          | 0.9091   |
| 0.1782        | 42.0  | 84   | 0.3967          | 0.8864   |
| 0.1782        | 43.0  | 86   | 0.4447          | 0.8636   |
| 0.1782        | 44.0  | 88   | 0.2020          | 0.9091   |
| 0.2059        | 45.0  | 90   | 0.1911          | 0.9318   |
| 0.2059        | 46.0  | 92   | 0.2609          | 0.9091   |
| 0.2059        | 47.0  | 94   | 0.2925          | 0.9091   |
| 0.2059        | 48.0  | 96   | 0.2079          | 0.9318   |
| 0.2059        | 49.0  | 98   | 0.1853          | 0.9318   |
| 0.1706        | 50.0  | 100  | 0.2860          | 0.9318   |
| 0.1706        | 51.0  | 102  | 0.3735          | 0.8636   |
| 0.1706        | 52.0  | 104  | 0.1968          | 0.9318   |
| 0.1706        | 53.0  | 106  | 0.1722          | 0.9318   |
| 0.1706        | 54.0  | 108  | 0.3123          | 0.8636   |
| 0.1429        | 55.0  | 110  | 0.3297          | 0.8864   |
| 0.1429        | 56.0  | 112  | 0.1430          | 0.9773   |
| 0.1429        | 57.0  | 114  | 0.1134          | 0.9773   |
| 0.1429        | 58.0  | 116  | 0.2312          | 0.9091   |
| 0.1429        | 59.0  | 118  | 0.2826          | 0.9091   |
| 0.1325        | 60.0  | 120  | 0.2417          | 0.9091   |
| 0.1325        | 61.0  | 122  | 0.1393          | 0.9318   |
| 0.1325        | 62.0  | 124  | 0.2178          | 0.9318   |
| 0.1325        | 63.0  | 126  | 0.3991          | 0.9091   |
| 0.1325        | 64.0  | 128  | 0.3325          | 0.9091   |
| 0.1481        | 65.0  | 130  | 0.2327          | 0.9091   |
| 0.1481        | 66.0  | 132  | 0.2885          | 0.9091   |
| 0.1481        | 67.0  | 134  | 0.3576          | 0.9091   |
| 0.1481        | 68.0  | 136  | 0.2686          | 0.9318   |
| 0.1481        | 69.0  | 138  | 0.1717          | 0.9545   |
| 0.1237        | 70.0  | 140  | 0.1493          | 0.9545   |
| 0.1237        | 71.0  | 142  | 0.1429          | 0.9318   |
| 0.1237        | 72.0  | 144  | 0.1790          | 0.9318   |
| 0.1237        | 73.0  | 146  | 0.1590          | 0.9318   |
| 0.1237        | 74.0  | 148  | 0.1971          | 0.8864   |
| 0.105         | 75.0  | 150  | 0.2229          | 0.9318   |
| 0.105         | 76.0  | 152  | 0.1789          | 0.8864   |
| 0.105         | 77.0  | 154  | 0.1671          | 0.9545   |
| 0.105         | 78.0  | 156  | 0.2435          | 0.9318   |
| 0.105         | 79.0  | 158  | 0.2658          | 0.9318   |
| 0.0923        | 80.0  | 160  | 0.2092          | 0.9318   |
| 0.0923        | 81.0  | 162  | 0.1748          | 0.9318   |
| 0.0923        | 82.0  | 164  | 0.1727          | 0.9318   |
| 0.0923        | 83.0  | 166  | 0.1945          | 0.9091   |
| 0.0923        | 84.0  | 168  | 0.2429          | 0.9318   |
| 0.1033        | 85.0  | 170  | 0.2796          | 0.9318   |
| 0.1033        | 86.0  | 172  | 0.2548          | 0.9318   |
| 0.1033        | 87.0  | 174  | 0.2379          | 0.9091   |
| 0.1033        | 88.0  | 176  | 0.2409          | 0.9091   |
| 0.1033        | 89.0  | 178  | 0.2421          | 0.9091   |
| 0.1073        | 90.0  | 180  | 0.2332          | 0.9091   |
| 0.1073        | 91.0  | 182  | 0.2231          | 0.9091   |
| 0.1073        | 92.0  | 184  | 0.2153          | 0.9318   |
| 0.1073        | 93.0  | 186  | 0.2088          | 0.9318   |
| 0.1073        | 94.0  | 188  | 0.2058          | 0.9318   |
| 0.104         | 95.0  | 190  | 0.2040          | 0.9318   |
| 0.104         | 96.0  | 192  | 0.2046          | 0.9318   |
| 0.104         | 97.0  | 194  | 0.2043          | 0.9318   |
| 0.104         | 98.0  | 196  | 0.2056          | 0.9318   |
| 0.104         | 99.0  | 198  | 0.2081          | 0.9318   |
| 0.0896        | 100.0 | 200  | 0.2097          | 0.9318   |


### Framework versions

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

hasta normal