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# swin-tiny-patch4-window7-224-finetuned-woody_130epochs

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: 0.4550
- Accuracy: 0.8921

## 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: 130

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.6694        | 1.0   | 58   | 0.6370          | 0.6594   |
| 0.6072        | 2.0   | 116  | 0.5813          | 0.7030   |
| 0.6048        | 3.0   | 174  | 0.5646          | 0.7030   |
| 0.5849        | 4.0   | 232  | 0.5778          | 0.6970   |
| 0.5671        | 5.0   | 290  | 0.5394          | 0.7236   |
| 0.5575        | 6.0   | 348  | 0.5212          | 0.7382   |
| 0.568         | 7.0   | 406  | 0.5218          | 0.7358   |
| 0.5607        | 8.0   | 464  | 0.5183          | 0.7527   |
| 0.5351        | 9.0   | 522  | 0.5138          | 0.7467   |
| 0.5459        | 10.0  | 580  | 0.5290          | 0.7394   |
| 0.5454        | 11.0  | 638  | 0.5212          | 0.7345   |
| 0.5291        | 12.0  | 696  | 0.5130          | 0.7576   |
| 0.5378        | 13.0  | 754  | 0.5372          | 0.7503   |
| 0.5264        | 14.0  | 812  | 0.6089          | 0.6861   |
| 0.4909        | 15.0  | 870  | 0.4852          | 0.7636   |
| 0.5591        | 16.0  | 928  | 0.4817          | 0.76     |
| 0.4966        | 17.0  | 986  | 0.5673          | 0.6933   |
| 0.4988        | 18.0  | 1044 | 0.5131          | 0.7418   |
| 0.5339        | 19.0  | 1102 | 0.4998          | 0.7394   |
| 0.4804        | 20.0  | 1160 | 0.4655          | 0.7733   |
| 0.503         | 21.0  | 1218 | 0.4554          | 0.7685   |
| 0.4859        | 22.0  | 1276 | 0.4713          | 0.7770   |
| 0.504         | 23.0  | 1334 | 0.4545          | 0.7721   |
| 0.478         | 24.0  | 1392 | 0.4658          | 0.7830   |
| 0.4759        | 25.0  | 1450 | 0.4365          | 0.8012   |
| 0.4686        | 26.0  | 1508 | 0.4452          | 0.7855   |
| 0.4668        | 27.0  | 1566 | 0.4427          | 0.7879   |
| 0.4615        | 28.0  | 1624 | 0.4439          | 0.7685   |
| 0.4588        | 29.0  | 1682 | 0.4378          | 0.7830   |
| 0.4588        | 30.0  | 1740 | 0.4229          | 0.7988   |
| 0.4296        | 31.0  | 1798 | 0.4188          | 0.7976   |
| 0.4208        | 32.0  | 1856 | 0.4316          | 0.7891   |
| 0.4481        | 33.0  | 1914 | 0.4331          | 0.7891   |
| 0.4253        | 34.0  | 1972 | 0.4524          | 0.7879   |
| 0.4117        | 35.0  | 2030 | 0.4570          | 0.7952   |
| 0.4405        | 36.0  | 2088 | 0.4307          | 0.7927   |
| 0.4154        | 37.0  | 2146 | 0.4257          | 0.8024   |
| 0.3962        | 38.0  | 2204 | 0.5077          | 0.7818   |
| 0.414         | 39.0  | 2262 | 0.4602          | 0.8012   |
| 0.3937        | 40.0  | 2320 | 0.4741          | 0.7770   |
| 0.4186        | 41.0  | 2378 | 0.4250          | 0.8      |
| 0.4076        | 42.0  | 2436 | 0.4353          | 0.7988   |
| 0.3777        | 43.0  | 2494 | 0.4442          | 0.7879   |
| 0.3968        | 44.0  | 2552 | 0.4525          | 0.7879   |
| 0.377         | 45.0  | 2610 | 0.4198          | 0.7988   |
| 0.378         | 46.0  | 2668 | 0.4297          | 0.8097   |
| 0.3675        | 47.0  | 2726 | 0.4435          | 0.8085   |
| 0.3562        | 48.0  | 2784 | 0.4477          | 0.7952   |
| 0.381         | 49.0  | 2842 | 0.4206          | 0.8255   |
| 0.3603        | 50.0  | 2900 | 0.4136          | 0.8109   |
| 0.3331        | 51.0  | 2958 | 0.4141          | 0.8230   |
| 0.3471        | 52.0  | 3016 | 0.4253          | 0.8109   |
| 0.346         | 53.0  | 3074 | 0.5203          | 0.8048   |
| 0.3481        | 54.0  | 3132 | 0.4288          | 0.8242   |
| 0.3411        | 55.0  | 3190 | 0.4416          | 0.8194   |
| 0.3275        | 56.0  | 3248 | 0.4149          | 0.8291   |
| 0.3067        | 57.0  | 3306 | 0.4623          | 0.8218   |
| 0.3166        | 58.0  | 3364 | 0.4432          | 0.8255   |
| 0.3294        | 59.0  | 3422 | 0.4599          | 0.8267   |
| 0.3146        | 60.0  | 3480 | 0.4266          | 0.8291   |
| 0.3091        | 61.0  | 3538 | 0.4318          | 0.8315   |
| 0.3277        | 62.0  | 3596 | 0.4252          | 0.8242   |
| 0.296         | 63.0  | 3654 | 0.4332          | 0.8436   |
| 0.3241        | 64.0  | 3712 | 0.4729          | 0.8194   |
| 0.3104        | 65.0  | 3770 | 0.4228          | 0.8448   |
| 0.2878        | 66.0  | 3828 | 0.4173          | 0.8388   |
| 0.265         | 67.0  | 3886 | 0.4210          | 0.8497   |
| 0.3011        | 68.0  | 3944 | 0.4276          | 0.8436   |
| 0.2861        | 69.0  | 4002 | 0.4923          | 0.8315   |
| 0.2994        | 70.0  | 4060 | 0.4472          | 0.8182   |
| 0.276         | 71.0  | 4118 | 0.4541          | 0.8315   |
| 0.2796        | 72.0  | 4176 | 0.4218          | 0.8521   |
| 0.2727        | 73.0  | 4234 | 0.4053          | 0.8448   |
| 0.255         | 74.0  | 4292 | 0.4356          | 0.8376   |
| 0.276         | 75.0  | 4350 | 0.4193          | 0.8436   |
| 0.261         | 76.0  | 4408 | 0.4484          | 0.8533   |
| 0.2416        | 77.0  | 4466 | 0.4722          | 0.8194   |
| 0.2602        | 78.0  | 4524 | 0.4431          | 0.8533   |
| 0.2591        | 79.0  | 4582 | 0.4269          | 0.8606   |
| 0.2613        | 80.0  | 4640 | 0.4335          | 0.8485   |
| 0.2555        | 81.0  | 4698 | 0.4269          | 0.8594   |
| 0.2832        | 82.0  | 4756 | 0.3968          | 0.8715   |
| 0.264         | 83.0  | 4814 | 0.4173          | 0.8703   |
| 0.2462        | 84.0  | 4872 | 0.4150          | 0.8606   |
| 0.2424        | 85.0  | 4930 | 0.4377          | 0.8630   |
| 0.2574        | 86.0  | 4988 | 0.4120          | 0.8679   |
| 0.2273        | 87.0  | 5046 | 0.4393          | 0.8533   |
| 0.2334        | 88.0  | 5104 | 0.4366          | 0.8630   |
| 0.2258        | 89.0  | 5162 | 0.4189          | 0.8630   |
| 0.2153        | 90.0  | 5220 | 0.4474          | 0.8630   |
| 0.2462        | 91.0  | 5278 | 0.4362          | 0.8642   |
| 0.2356        | 92.0  | 5336 | 0.4454          | 0.8715   |
| 0.2019        | 93.0  | 5394 | 0.4413          | 0.88     |
| 0.209         | 94.0  | 5452 | 0.4410          | 0.8703   |
| 0.2201        | 95.0  | 5510 | 0.4323          | 0.8691   |
| 0.2245        | 96.0  | 5568 | 0.4999          | 0.8618   |
| 0.2178        | 97.0  | 5626 | 0.4612          | 0.8655   |
| 0.2163        | 98.0  | 5684 | 0.4340          | 0.8703   |
| 0.2228        | 99.0  | 5742 | 0.4504          | 0.8788   |
| 0.2151        | 100.0 | 5800 | 0.4602          | 0.8703   |
| 0.1988        | 101.0 | 5858 | 0.4414          | 0.8812   |
| 0.2227        | 102.0 | 5916 | 0.4392          | 0.8824   |
| 0.1772        | 103.0 | 5974 | 0.5069          | 0.8630   |
| 0.2199        | 104.0 | 6032 | 0.4648          | 0.8667   |
| 0.1936        | 105.0 | 6090 | 0.4806          | 0.8691   |
| 0.199         | 106.0 | 6148 | 0.4569          | 0.8764   |
| 0.2149        | 107.0 | 6206 | 0.4445          | 0.8739   |
| 0.1917        | 108.0 | 6264 | 0.4444          | 0.8727   |
| 0.201         | 109.0 | 6322 | 0.4594          | 0.8727   |
| 0.1938        | 110.0 | 6380 | 0.4564          | 0.8764   |
| 0.1977        | 111.0 | 6438 | 0.4398          | 0.8739   |
| 0.1776        | 112.0 | 6496 | 0.4356          | 0.88     |
| 0.1939        | 113.0 | 6554 | 0.4412          | 0.8848   |
| 0.178         | 114.0 | 6612 | 0.4373          | 0.88     |
| 0.1926        | 115.0 | 6670 | 0.4508          | 0.8812   |
| 0.1979        | 116.0 | 6728 | 0.4477          | 0.8848   |
| 0.1958        | 117.0 | 6786 | 0.4488          | 0.8897   |
| 0.189         | 118.0 | 6844 | 0.4553          | 0.8836   |
| 0.1838        | 119.0 | 6902 | 0.4605          | 0.8848   |
| 0.1755        | 120.0 | 6960 | 0.4463          | 0.8836   |
| 0.1958        | 121.0 | 7018 | 0.4474          | 0.8861   |
| 0.1857        | 122.0 | 7076 | 0.4550          | 0.8921   |
| 0.1466        | 123.0 | 7134 | 0.4494          | 0.8885   |
| 0.1751        | 124.0 | 7192 | 0.4560          | 0.8873   |
| 0.175         | 125.0 | 7250 | 0.4383          | 0.8897   |
| 0.207         | 126.0 | 7308 | 0.4601          | 0.8873   |
| 0.1756        | 127.0 | 7366 | 0.4425          | 0.8897   |
| 0.1695        | 128.0 | 7424 | 0.4533          | 0.8909   |
| 0.1873        | 129.0 | 7482 | 0.4510          | 0.8897   |
| 0.1726        | 130.0 | 7540 | 0.4463          | 0.8909   |


### Framework versions

- Transformers 4.23.1
- Pytorch 1.12.1+cu113
- Datasets 2.6.1
- Tokenizers 0.13.1

normal woody