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# beit-base-patch16-224-85-fold3

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: 0.3297
- Accuracy: 0.9091

## 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    | 0.6425          | 0.6136   |
| No log        | 2.0   | 4    | 0.6036          | 0.7273   |
| No log        | 3.0   | 6    | 0.5549          | 0.7045   |
| No log        | 4.0   | 8    | 0.4879          | 0.7273   |
| 0.5424        | 5.0   | 10   | 0.7873          | 0.7045   |
| 0.5424        | 6.0   | 12   | 0.6817          | 0.7045   |
| 0.5424        | 7.0   | 14   | 0.4846          | 0.75     |
| 0.5424        | 8.0   | 16   | 0.5266          | 0.7273   |
| 0.5424        | 9.0   | 18   | 0.4487          | 0.7727   |
| 0.5207        | 10.0  | 20   | 0.3768          | 0.8182   |
| 0.5207        | 11.0  | 22   | 0.6762          | 0.7045   |
| 0.5207        | 12.0  | 24   | 0.3988          | 0.8409   |
| 0.5207        | 13.0  | 26   | 0.3812          | 0.8864   |
| 0.5207        | 14.0  | 28   | 0.4207          | 0.7727   |
| 0.386         | 15.0  | 30   | 0.3801          | 0.8182   |
| 0.386         | 16.0  | 32   | 0.5402          | 0.7045   |
| 0.386         | 17.0  | 34   | 0.3865          | 0.8636   |
| 0.386         | 18.0  | 36   | 0.3635          | 0.8182   |
| 0.386         | 19.0  | 38   | 0.5374          | 0.7273   |
| 0.3232        | 20.0  | 40   | 0.5088          | 0.75     |
| 0.3232        | 21.0  | 42   | 0.3507          | 0.8182   |
| 0.3232        | 22.0  | 44   | 0.2995          | 0.8409   |
| 0.3232        | 23.0  | 46   | 0.3403          | 0.8409   |
| 0.3232        | 24.0  | 48   | 0.3858          | 0.8182   |
| 0.249         | 25.0  | 50   | 0.4126          | 0.7727   |
| 0.249         | 26.0  | 52   | 0.4907          | 0.8182   |
| 0.249         | 27.0  | 54   | 0.3799          | 0.8182   |
| 0.249         | 28.0  | 56   | 0.3528          | 0.8182   |
| 0.249         | 29.0  | 58   | 0.3775          | 0.8182   |
| 0.2064        | 30.0  | 60   | 0.3520          | 0.8182   |
| 0.2064        | 31.0  | 62   | 0.4397          | 0.7727   |
| 0.2064        | 32.0  | 64   | 0.4284          | 0.75     |
| 0.2064        | 33.0  | 66   | 0.3833          | 0.8409   |
| 0.2064        | 34.0  | 68   | 0.3558          | 0.8409   |
| 0.2066        | 35.0  | 70   | 0.4880          | 0.8182   |
| 0.2066        | 36.0  | 72   | 0.3739          | 0.8182   |
| 0.2066        | 37.0  | 74   | 0.5409          | 0.7727   |
| 0.2066        | 38.0  | 76   | 0.4869          | 0.8182   |
| 0.2066        | 39.0  | 78   | 0.8398          | 0.75     |
| 0.1776        | 40.0  | 80   | 0.5410          | 0.7955   |
| 0.1776        | 41.0  | 82   | 0.4740          | 0.8409   |
| 0.1776        | 42.0  | 84   | 0.3428          | 0.8636   |
| 0.1776        | 43.0  | 86   | 0.3135          | 0.8864   |
| 0.1776        | 44.0  | 88   | 0.3297          | 0.9091   |
| 0.1732        | 45.0  | 90   | 0.3982          | 0.9091   |
| 0.1732        | 46.0  | 92   | 0.5961          | 0.7955   |
| 0.1732        | 47.0  | 94   | 0.4798          | 0.8864   |
| 0.1732        | 48.0  | 96   | 0.5187          | 0.8182   |
| 0.1732        | 49.0  | 98   | 0.4430          | 0.9091   |
| 0.1372        | 50.0  | 100  | 0.4522          | 0.9091   |
| 0.1372        | 51.0  | 102  | 0.5617          | 0.8409   |
| 0.1372        | 52.0  | 104  | 0.6568          | 0.8182   |
| 0.1372        | 53.0  | 106  | 0.8141          | 0.7955   |
| 0.1372        | 54.0  | 108  | 0.6189          | 0.8409   |
| 0.1305        | 55.0  | 110  | 0.5124          | 0.8636   |
| 0.1305        | 56.0  | 112  | 0.5095          | 0.8636   |
| 0.1305        | 57.0  | 114  | 0.4101          | 0.8864   |
| 0.1305        | 58.0  | 116  | 0.7712          | 0.7727   |
| 0.1305        | 59.0  | 118  | 0.5073          | 0.7955   |
| 0.1423        | 60.0  | 120  | 0.3890          | 0.8636   |
| 0.1423        | 61.0  | 122  | 0.5701          | 0.8182   |
| 0.1423        | 62.0  | 124  | 0.5482          | 0.8409   |
| 0.1423        | 63.0  | 126  | 0.5508          | 0.8409   |
| 0.1423        | 64.0  | 128  | 0.6589          | 0.7955   |
| 0.13          | 65.0  | 130  | 0.7184          | 0.75     |
| 0.13          | 66.0  | 132  | 0.4702          | 0.8864   |
| 0.13          | 67.0  | 134  | 0.4339          | 0.9091   |
| 0.13          | 68.0  | 136  | 0.4463          | 0.9091   |
| 0.13          | 69.0  | 138  | 0.4887          | 0.8864   |
| 0.1232        | 70.0  | 140  | 0.5121          | 0.8636   |
| 0.1232        | 71.0  | 142  | 0.4944          | 0.9091   |
| 0.1232        | 72.0  | 144  | 0.5208          | 0.8864   |
| 0.1232        | 73.0  | 146  | 0.6074          | 0.8182   |
| 0.1232        | 74.0  | 148  | 0.8013          | 0.75     |
| 0.1241        | 75.0  | 150  | 0.7022          | 0.7727   |
| 0.1241        | 76.0  | 152  | 0.5641          | 0.8864   |
| 0.1241        | 77.0  | 154  | 0.6550          | 0.8409   |
| 0.1241        | 78.0  | 156  | 0.6268          | 0.8409   |
| 0.1241        | 79.0  | 158  | 0.5466          | 0.8864   |
| 0.1254        | 80.0  | 160  | 0.5453          | 0.8864   |
| 0.1254        | 81.0  | 162  | 0.5663          | 0.8636   |
| 0.1254        | 82.0  | 164  | 0.5377          | 0.8409   |
| 0.1254        | 83.0  | 166  | 0.5381          | 0.8864   |
| 0.1254        | 84.0  | 168  | 0.5459          | 0.8636   |
| 0.1061        | 85.0  | 170  | 0.5490          | 0.8636   |
| 0.1061        | 86.0  | 172  | 0.5444          | 0.8636   |
| 0.1061        | 87.0  | 174  | 0.5344          | 0.8636   |
| 0.1061        | 88.0  | 176  | 0.5251          | 0.8636   |
| 0.1061        | 89.0  | 178  | 0.5178          | 0.8864   |
| 0.1084        | 90.0  | 180  | 0.5161          | 0.8864   |
| 0.1084        | 91.0  | 182  | 0.5184          | 0.8864   |
| 0.1084        | 92.0  | 184  | 0.5185          | 0.8864   |
| 0.1084        | 93.0  | 186  | 0.5300          | 0.8636   |
| 0.1084        | 94.0  | 188  | 0.5599          | 0.8636   |
| 0.1025        | 95.0  | 190  | 0.5972          | 0.8182   |
| 0.1025        | 96.0  | 192  | 0.6083          | 0.8182   |
| 0.1025        | 97.0  | 194  | 0.5969          | 0.8409   |
| 0.1025        | 98.0  | 196  | 0.5769          | 0.8636   |
| 0.1025        | 99.0  | 198  | 0.5673          | 0.8636   |
| 0.1184        | 100.0 | 200  | 0.5642          | 0.8636   |


### Framework versions

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

hasta normal