
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# swin-tiny-patch4-window7-224-finetuned-ADC-3cls-0922

This model is a fine-tuned version of [microsoft/swin-tiny-patch4-window7-224](https://huggingface.co/microsoft/swin-tiny-patch4-window7-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6771
- Accuracy: 0.8286

## 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: 0.0001
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 256
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.2
- num_epochs: 200

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 2    | 0.6875          | 0.8143   |
| No log        | 2.0   | 4    | 0.6874          | 0.8143   |
| No log        | 3.0   | 6    | 0.6873          | 0.8143   |
| No log        | 4.0   | 8    | 0.6871          | 0.8143   |
| 0.7555        | 5.0   | 10   | 0.6869          | 0.8143   |
| 0.7555        | 6.0   | 12   | 0.6866          | 0.8143   |
| 0.7555        | 7.0   | 14   | 0.6862          | 0.8143   |
| 0.7555        | 8.0   | 16   | 0.6858          | 0.8143   |
| 0.7555        | 9.0   | 18   | 0.6853          | 0.8143   |
| 0.7576        | 10.0  | 20   | 0.6848          | 0.8143   |
| 0.7576        | 11.0  | 22   | 0.6842          | 0.8143   |
| 0.7576        | 12.0  | 24   | 0.6836          | 0.8143   |
| 0.7576        | 13.0  | 26   | 0.6830          | 0.8143   |
| 0.7576        | 14.0  | 28   | 0.6823          | 0.8143   |
| 0.769         | 15.0  | 30   | 0.6816          | 0.8      |
| 0.769         | 16.0  | 32   | 0.6808          | 0.8      |
| 0.769         | 17.0  | 34   | 0.6800          | 0.8143   |
| 0.769         | 18.0  | 36   | 0.6791          | 0.8143   |
| 0.769         | 19.0  | 38   | 0.6781          | 0.8143   |
| 0.7564        | 20.0  | 40   | 0.6771          | 0.8286   |
| 0.7564        | 21.0  | 42   | 0.6760          | 0.8143   |
| 0.7564        | 22.0  | 44   | 0.6748          | 0.8143   |
| 0.7564        | 23.0  | 46   | 0.6737          | 0.8      |
| 0.7564        | 24.0  | 48   | 0.6725          | 0.8      |
| 0.7508        | 25.0  | 50   | 0.6713          | 0.8143   |
| 0.7508        | 26.0  | 52   | 0.6701          | 0.8143   |
| 0.7508        | 27.0  | 54   | 0.6689          | 0.8143   |
| 0.7508        | 28.0  | 56   | 0.6674          | 0.8143   |
| 0.7508        | 29.0  | 58   | 0.6660          | 0.8143   |
| 0.747         | 30.0  | 60   | 0.6646          | 0.8143   |
| 0.747         | 31.0  | 62   | 0.6631          | 0.8143   |
| 0.747         | 32.0  | 64   | 0.6616          | 0.8143   |
| 0.747         | 33.0  | 66   | 0.6601          | 0.8143   |
| 0.747         | 34.0  | 68   | 0.6586          | 0.8143   |
| 0.7343        | 35.0  | 70   | 0.6570          | 0.8143   |
| 0.7343        | 36.0  | 72   | 0.6553          | 0.8143   |
| 0.7343        | 37.0  | 74   | 0.6536          | 0.8143   |
| 0.7343        | 38.0  | 76   | 0.6517          | 0.8143   |
| 0.7343        | 39.0  | 78   | 0.6499          | 0.8143   |
| 0.7532        | 40.0  | 80   | 0.6480          | 0.8143   |
| 0.7532        | 41.0  | 82   | 0.6461          | 0.8143   |
| 0.7532        | 42.0  | 84   | 0.6442          | 0.8143   |
| 0.7532        | 43.0  | 86   | 0.6423          | 0.8143   |
| 0.7532        | 44.0  | 88   | 0.6405          | 0.8143   |
| 0.7239        | 45.0  | 90   | 0.6387          | 0.8143   |
| 0.7239        | 46.0  | 92   | 0.6368          | 0.8143   |
| 0.7239        | 47.0  | 94   | 0.6352          | 0.8143   |
| 0.7239        | 48.0  | 96   | 0.6337          | 0.8143   |
| 0.7239        | 49.0  | 98   | 0.6321          | 0.8286   |
| 0.7085        | 50.0  | 100  | 0.6307          | 0.8286   |
| 0.7085        | 51.0  | 102  | 0.6294          | 0.8286   |
| 0.7085        | 52.0  | 104  | 0.6278          | 0.8286   |
| 0.7085        | 53.0  | 106  | 0.6263          | 0.8286   |
| 0.7085        | 54.0  | 108  | 0.6248          | 0.8143   |
| 0.7203        | 55.0  | 110  | 0.6233          | 0.8143   |
| 0.7203        | 56.0  | 112  | 0.6219          | 0.8143   |
| 0.7203        | 57.0  | 114  | 0.6205          | 0.8143   |
| 0.7203        | 58.0  | 116  | 0.6191          | 0.8143   |
| 0.7203        | 59.0  | 118  | 0.6179          | 0.8143   |
| 0.7136        | 60.0  | 120  | 0.6167          | 0.8143   |
| 0.7136        | 61.0  | 122  | 0.6157          | 0.8143   |
| 0.7136        | 62.0  | 124  | 0.6148          | 0.8      |
| 0.7136        | 63.0  | 126  | 0.6138          | 0.8      |
| 0.7136        | 64.0  | 128  | 0.6125          | 0.8      |
| 0.7123        | 65.0  | 130  | 0.6111          | 0.8      |
| 0.7123        | 66.0  | 132  | 0.6096          | 0.8143   |
| 0.7123        | 67.0  | 134  | 0.6083          | 0.8143   |
| 0.7123        | 68.0  | 136  | 0.6070          | 0.8143   |
| 0.7123        | 69.0  | 138  | 0.6057          | 0.8143   |
| 0.7076        | 70.0  | 140  | 0.6046          | 0.8143   |
| 0.7076        | 71.0  | 142  | 0.6035          | 0.8143   |
| 0.7076        | 72.0  | 144  | 0.6023          | 0.8143   |
| 0.7076        | 73.0  | 146  | 0.6011          | 0.8143   |
| 0.7076        | 74.0  | 148  | 0.5999          | 0.8143   |
| 0.6878        | 75.0  | 150  | 0.5988          | 0.8143   |
| 0.6878        | 76.0  | 152  | 0.5975          | 0.8143   |
| 0.6878        | 77.0  | 154  | 0.5964          | 0.8143   |
| 0.6878        | 78.0  | 156  | 0.5953          | 0.8143   |
| 0.6878        | 79.0  | 158  | 0.5942          | 0.8143   |
| 0.6657        | 80.0  | 160  | 0.5932          | 0.8143   |
| 0.6657        | 81.0  | 162  | 0.5923          | 0.8143   |
| 0.6657        | 82.0  | 164  | 0.5914          | 0.8143   |
| 0.6657        | 83.0  | 166  | 0.5906          | 0.8143   |
| 0.6657        | 84.0  | 168  | 0.5897          | 0.8143   |
| 0.6434        | 85.0  | 170  | 0.5888          | 0.8143   |
| 0.6434        | 86.0  | 172  | 0.5878          | 0.8143   |
| 0.6434        | 87.0  | 174  | 0.5868          | 0.8143   |
| 0.6434        | 88.0  | 176  | 0.5859          | 0.8143   |
| 0.6434        | 89.0  | 178  | 0.5851          | 0.8143   |
| 0.6825        | 90.0  | 180  | 0.5843          | 0.8143   |
| 0.6825        | 91.0  | 182  | 0.5836          | 0.8143   |
| 0.6825        | 92.0  | 184  | 0.5828          | 0.8143   |
| 0.6825        | 93.0  | 186  | 0.5823          | 0.8143   |
| 0.6825        | 94.0  | 188  | 0.5817          | 0.8286   |
| 0.6695        | 95.0  | 190  | 0.5809          | 0.8143   |
| 0.6695        | 96.0  | 192  | 0.5801          | 0.8143   |
| 0.6695        | 97.0  | 194  | 0.5793          | 0.8143   |
| 0.6695        | 98.0  | 196  | 0.5787          | 0.8143   |
| 0.6695        | 99.0  | 198  | 0.5780          | 0.8143   |
| 0.6672        | 100.0 | 200  | 0.5772          | 0.8143   |
| 0.6672        | 101.0 | 202  | 0.5762          | 0.8143   |
| 0.6672        | 102.0 | 204  | 0.5754          | 0.8143   |
| 0.6672        | 103.0 | 206  | 0.5746          | 0.8143   |
| 0.6672        | 104.0 | 208  | 0.5738          | 0.8143   |
| 0.6569        | 105.0 | 210  | 0.5731          | 0.8143   |
| 0.6569        | 106.0 | 212  | 0.5724          | 0.8143   |
| 0.6569        | 107.0 | 214  | 0.5716          | 0.8143   |
| 0.6569        | 108.0 | 216  | 0.5708          | 0.8143   |
| 0.6569        | 109.0 | 218  | 0.5701          | 0.8143   |
| 0.6748        | 110.0 | 220  | 0.5694          | 0.8143   |
| 0.6748        | 111.0 | 222  | 0.5687          | 0.8143   |
| 0.6748        | 112.0 | 224  | 0.5680          | 0.8143   |
| 0.6748        | 113.0 | 226  | 0.5674          | 0.8143   |
| 0.6748        | 114.0 | 228  | 0.5668          | 0.8143   |
| 0.6388        | 115.0 | 230  | 0.5662          | 0.8143   |
| 0.6388        | 116.0 | 232  | 0.5657          | 0.8143   |
| 0.6388        | 117.0 | 234  | 0.5652          | 0.8143   |
| 0.6388        | 118.0 | 236  | 0.5648          | 0.8286   |
| 0.6388        | 119.0 | 238  | 0.5645          | 0.8286   |
| 0.6551        | 120.0 | 240  | 0.5641          | 0.8286   |
| 0.6551        | 121.0 | 242  | 0.5636          | 0.8143   |
| 0.6551        | 122.0 | 244  | 0.5631          | 0.8143   |
| 0.6551        | 123.0 | 246  | 0.5627          | 0.8143   |
| 0.6551        | 124.0 | 248  | 0.5624          | 0.8143   |
| 0.6452        | 125.0 | 250  | 0.5622          | 0.8143   |
| 0.6452        | 126.0 | 252  | 0.5620          | 0.8143   |
| 0.6452        | 127.0 | 254  | 0.5618          | 0.8143   |
| 0.6452        | 128.0 | 256  | 0.5615          | 0.8143   |
| 0.6452        | 129.0 | 258  | 0.5613          | 0.8143   |
| 0.645         | 130.0 | 260  | 0.5611          | 0.8143   |
| 0.645         | 131.0 | 262  | 0.5608          | 0.8143   |
| 0.645         | 132.0 | 264  | 0.5606          | 0.8143   |
| 0.645         | 133.0 | 266  | 0.5602          | 0.8143   |
| 0.645         | 134.0 | 268  | 0.5596          | 0.8143   |
| 0.629         | 135.0 | 270  | 0.5590          | 0.8143   |
| 0.629         | 136.0 | 272  | 0.5582          | 0.8143   |
| 0.629         | 137.0 | 274  | 0.5576          | 0.8143   |
| 0.629         | 138.0 | 276  | 0.5571          | 0.8143   |
| 0.629         | 139.0 | 278  | 0.5568          | 0.8143   |
| 0.7126        | 140.0 | 280  | 0.5565          | 0.8143   |
| 0.7126        | 141.0 | 282  | 0.5563          | 0.8143   |
| 0.7126        | 142.0 | 284  | 0.5561          | 0.8143   |
| 0.7126        | 143.0 | 286  | 0.5559          | 0.8143   |
| 0.7126        | 144.0 | 288  | 0.5555          | 0.8143   |
| 0.669         | 145.0 | 290  | 0.5552          | 0.8143   |
| 0.669         | 146.0 | 292  | 0.5547          | 0.8143   |
| 0.669         | 147.0 | 294  | 0.5542          | 0.8143   |
| 0.669         | 148.0 | 296  | 0.5538          | 0.8143   |
| 0.669         | 149.0 | 298  | 0.5534          | 0.8143   |
| 0.6481        | 150.0 | 300  | 0.5530          | 0.8143   |
| 0.6481        | 151.0 | 302  | 0.5526          | 0.8143   |
| 0.6481        | 152.0 | 304  | 0.5522          | 0.8143   |
| 0.6481        | 153.0 | 306  | 0.5519          | 0.8143   |
| 0.6481        | 154.0 | 308  | 0.5515          | 0.8143   |
| 0.6211        | 155.0 | 310  | 0.5510          | 0.8143   |
| 0.6211        | 156.0 | 312  | 0.5506          | 0.8143   |
| 0.6211        | 157.0 | 314  | 0.5502          | 0.8143   |
| 0.6211        | 158.0 | 316  | 0.5499          | 0.8143   |
| 0.6211        | 159.0 | 318  | 0.5496          | 0.8143   |
| 0.6458        | 160.0 | 320  | 0.5492          | 0.8286   |
| 0.6458        | 161.0 | 322  | 0.5490          | 0.8143   |
| 0.6458        | 162.0 | 324  | 0.5488          | 0.8143   |
| 0.6458        | 163.0 | 326  | 0.5486          | 0.8143   |
| 0.6458        | 164.0 | 328  | 0.5484          | 0.8143   |
| 0.6317        | 165.0 | 330  | 0.5481          | 0.8143   |
| 0.6317        | 166.0 | 332  | 0.5479          | 0.8286   |
| 0.6317        | 167.0 | 334  | 0.5476          | 0.8286   |
| 0.6317        | 168.0 | 336  | 0.5473          | 0.8286   |
| 0.6317        | 169.0 | 338  | 0.5471          | 0.8286   |
| 0.6154        | 170.0 | 340  | 0.5470          | 0.8286   |
| 0.6154        | 171.0 | 342  | 0.5468          | 0.8286   |
| 0.6154        | 172.0 | 344  | 0.5466          | 0.8286   |
| 0.6154        | 173.0 | 346  | 0.5464          | 0.8286   |
| 0.6154        | 174.0 | 348  | 0.5462          | 0.8286   |
| 0.6323        | 175.0 | 350  | 0.5460          | 0.8286   |
| 0.6323        | 176.0 | 352  | 0.5459          | 0.8286   |
| 0.6323        | 177.0 | 354  | 0.5457          | 0.8286   |
| 0.6323        | 178.0 | 356  | 0.5456          | 0.8286   |
| 0.6323        | 179.0 | 358  | 0.5455          | 0.8286   |
| 0.6331        | 180.0 | 360  | 0.5453          | 0.8286   |
| 0.6331        | 181.0 | 362  | 0.5452          | 0.8286   |
| 0.6331        | 182.0 | 364  | 0.5451          | 0.8286   |
| 0.6331        | 183.0 | 366  | 0.5449          | 0.8286   |
| 0.6331        | 184.0 | 368  | 0.5448          | 0.8286   |
| 0.6333        | 185.0 | 370  | 0.5447          | 0.8286   |
| 0.6333        | 186.0 | 372  | 0.5447          | 0.8286   |
| 0.6333        | 187.0 | 374  | 0.5446          | 0.8286   |
| 0.6333        | 188.0 | 376  | 0.5445          | 0.8286   |
| 0.6333        | 189.0 | 378  | 0.5445          | 0.8286   |
| 0.608         | 190.0 | 380  | 0.5444          | 0.8286   |
| 0.608         | 191.0 | 382  | 0.5444          | 0.8286   |
| 0.608         | 192.0 | 384  | 0.5443          | 0.8286   |
| 0.608         | 193.0 | 386  | 0.5443          | 0.8286   |
| 0.608         | 194.0 | 388  | 0.5442          | 0.8286   |
| 0.6155        | 195.0 | 390  | 0.5442          | 0.8286   |
| 0.6155        | 196.0 | 392  | 0.5442          | 0.8286   |
| 0.6155        | 197.0 | 394  | 0.5442          | 0.8286   |
| 0.6155        | 198.0 | 396  | 0.5441          | 0.8286   |
| 0.6155        | 199.0 | 398  | 0.5441          | 0.8286   |
| 0.6272        | 200.0 | 400  | 0.5441          | 0.8286   |


### Framework versions

- Transformers 4.33.2
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3

color pattern_fail residue