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# beit-base-patch16-224-85-fold2

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: 0.2763
- 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    | 0.6057          | 0.7273   |
| No log        | 2.0   | 4    | 0.6639          | 0.7045   |
| No log        | 3.0   | 6    | 0.7324          | 0.7045   |
| No log        | 4.0   | 8    | 0.5213          | 0.7273   |
| 0.5701        | 5.0   | 10   | 0.4717          | 0.8182   |
| 0.5701        | 6.0   | 12   | 0.5339          | 0.7045   |
| 0.5701        | 7.0   | 14   | 0.4959          | 0.7273   |
| 0.5701        | 8.0   | 16   | 0.4086          | 0.8409   |
| 0.5701        | 9.0   | 18   | 0.4039          | 0.8182   |
| 0.4248        | 10.0  | 20   | 0.4106          | 0.8182   |
| 0.4248        | 11.0  | 22   | 0.4108          | 0.8409   |
| 0.4248        | 12.0  | 24   | 0.4607          | 0.7727   |
| 0.4248        | 13.0  | 26   | 0.4446          | 0.7727   |
| 0.4248        | 14.0  | 28   | 0.3912          | 0.8409   |
| 0.3579        | 15.0  | 30   | 0.5183          | 0.7727   |
| 0.3579        | 16.0  | 32   | 0.2991          | 0.8864   |
| 0.3579        | 17.0  | 34   | 0.3587          | 0.8182   |
| 0.3579        | 18.0  | 36   | 0.3110          | 0.8182   |
| 0.3579        | 19.0  | 38   | 0.3084          | 0.8636   |
| 0.2838        | 20.0  | 40   | 0.3079          | 0.8864   |
| 0.2838        | 21.0  | 42   | 0.3033          | 0.8409   |
| 0.2838        | 22.0  | 44   | 0.3126          | 0.8409   |
| 0.2838        | 23.0  | 46   | 0.3171          | 0.8864   |
| 0.2838        | 24.0  | 48   | 0.2689          | 0.8636   |
| 0.2705        | 25.0  | 50   | 0.3175          | 0.8409   |
| 0.2705        | 26.0  | 52   | 0.3464          | 0.8409   |
| 0.2705        | 27.0  | 54   | 0.3092          | 0.8636   |
| 0.2705        | 28.0  | 56   | 0.3178          | 0.8636   |
| 0.2705        | 29.0  | 58   | 0.4107          | 0.7955   |
| 0.1887        | 30.0  | 60   | 0.4151          | 0.8182   |
| 0.1887        | 31.0  | 62   | 0.5450          | 0.7955   |
| 0.1887        | 32.0  | 64   | 0.2892          | 0.8409   |
| 0.1887        | 33.0  | 66   | 0.4078          | 0.8409   |
| 0.1887        | 34.0  | 68   | 0.2821          | 0.8636   |
| 0.1692        | 35.0  | 70   | 0.2708          | 0.8636   |
| 0.1692        | 36.0  | 72   | 0.2692          | 0.8864   |
| 0.1692        | 37.0  | 74   | 0.2806          | 0.8864   |
| 0.1692        | 38.0  | 76   | 0.4613          | 0.8182   |
| 0.1692        | 39.0  | 78   | 0.2887          | 0.9091   |
| 0.1623        | 40.0  | 80   | 0.4046          | 0.8409   |
| 0.1623        | 41.0  | 82   | 0.4542          | 0.8409   |
| 0.1623        | 42.0  | 84   | 0.3010          | 0.8636   |
| 0.1623        | 43.0  | 86   | 0.2954          | 0.8636   |
| 0.1623        | 44.0  | 88   | 0.2838          | 0.8864   |
| 0.1522        | 45.0  | 90   | 0.2675          | 0.8864   |
| 0.1522        | 46.0  | 92   | 0.2517          | 0.9091   |
| 0.1522        | 47.0  | 94   | 0.2687          | 0.9091   |
| 0.1522        | 48.0  | 96   | 0.2551          | 0.9091   |
| 0.1522        | 49.0  | 98   | 0.2661          | 0.8864   |
| 0.1379        | 50.0  | 100  | 0.3507          | 0.8182   |
| 0.1379        | 51.0  | 102  | 0.2629          | 0.8864   |
| 0.1379        | 52.0  | 104  | 0.2697          | 0.8864   |
| 0.1379        | 53.0  | 106  | 0.3081          | 0.8636   |
| 0.1379        | 54.0  | 108  | 0.3851          | 0.8409   |
| 0.1283        | 55.0  | 110  | 0.3104          | 0.8636   |
| 0.1283        | 56.0  | 112  | 0.3624          | 0.8864   |
| 0.1283        | 57.0  | 114  | 0.3199          | 0.8864   |
| 0.1283        | 58.0  | 116  | 0.4964          | 0.8182   |
| 0.1283        | 59.0  | 118  | 0.3356          | 0.8864   |
| 0.1335        | 60.0  | 120  | 0.2314          | 0.9091   |
| 0.1335        | 61.0  | 122  | 0.2334          | 0.9091   |
| 0.1335        | 62.0  | 124  | 0.3961          | 0.8636   |
| 0.1335        | 63.0  | 126  | 0.3453          | 0.8636   |
| 0.1335        | 64.0  | 128  | 0.2806          | 0.8636   |
| 0.1353        | 65.0  | 130  | 0.3372          | 0.8636   |
| 0.1353        | 66.0  | 132  | 0.2675          | 0.8864   |
| 0.1353        | 67.0  | 134  | 0.3482          | 0.8864   |
| 0.1353        | 68.0  | 136  | 0.3725          | 0.8636   |
| 0.1353        | 69.0  | 138  | 0.3769          | 0.8636   |
| 0.099         | 70.0  | 140  | 0.5170          | 0.8409   |
| 0.099         | 71.0  | 142  | 0.4710          | 0.8636   |
| 0.099         | 72.0  | 144  | 0.3266          | 0.9091   |
| 0.099         | 73.0  | 146  | 0.3390          | 0.8636   |
| 0.099         | 74.0  | 148  | 0.3051          | 0.8636   |
| 0.1179        | 75.0  | 150  | 0.3030          | 0.9091   |
| 0.1179        | 76.0  | 152  | 0.3208          | 0.9091   |
| 0.1179        | 77.0  | 154  | 0.2954          | 0.9091   |
| 0.1179        | 78.0  | 156  | 0.2777          | 0.9091   |
| 0.1179        | 79.0  | 158  | 0.2763          | 0.9318   |
| 0.1077        | 80.0  | 160  | 0.3059          | 0.9091   |
| 0.1077        | 81.0  | 162  | 0.3445          | 0.8864   |
| 0.1077        | 82.0  | 164  | 0.3239          | 0.9091   |
| 0.1077        | 83.0  | 166  | 0.3175          | 0.9091   |
| 0.1077        | 84.0  | 168  | 0.3214          | 0.9091   |
| 0.0907        | 85.0  | 170  | 0.3313          | 0.9091   |
| 0.0907        | 86.0  | 172  | 0.3492          | 0.9091   |
| 0.0907        | 87.0  | 174  | 0.3644          | 0.9091   |
| 0.0907        | 88.0  | 176  | 0.3637          | 0.9091   |
| 0.0907        | 89.0  | 178  | 0.3750          | 0.9091   |
| 0.0972        | 90.0  | 180  | 0.3845          | 0.9091   |
| 0.0972        | 91.0  | 182  | 0.3749          | 0.9091   |
| 0.0972        | 92.0  | 184  | 0.3721          | 0.8864   |
| 0.0972        | 93.0  | 186  | 0.3680          | 0.8864   |
| 0.0972        | 94.0  | 188  | 0.3634          | 0.8864   |
| 0.0733        | 95.0  | 190  | 0.3565          | 0.9091   |
| 0.0733        | 96.0  | 192  | 0.3519          | 0.9091   |
| 0.0733        | 97.0  | 194  | 0.3529          | 0.9091   |
| 0.0733        | 98.0  | 196  | 0.3536          | 0.9091   |
| 0.0733        | 99.0  | 198  | 0.3561          | 0.9091   |
| 0.079         | 100.0 | 200  | 0.3565          | 0.9091   |


### Framework versions

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

hasta normal