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# cards_bottom_left_swin-tiny-patch4-window7-224-finetuned-dough_100_epochs

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: 1.0025
- Accuracy: 0.5947

## 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 |
|:-------------:|:-----:|:------:|:---------------:|:--------:|
| 1.6956        | 1.0   | 1252   | 1.4843          | 0.3970   |
| 1.5633        | 2.0   | 2504   | 1.2584          | 0.4782   |
| 1.5568        | 3.0   | 3756   | 1.1976          | 0.4918   |
| 1.4727        | 4.0   | 5009   | 1.1884          | 0.4916   |
| 1.468         | 5.0   | 6261   | 1.1909          | 0.4889   |
| 1.4663        | 6.0   | 7513   | 1.1263          | 0.5288   |
| 1.4409        | 7.0   | 8765   | 1.0967          | 0.5441   |
| 1.4329        | 8.0   | 10018  | 1.0976          | 0.5388   |
| 1.4842        | 9.0   | 11270  | 1.1076          | 0.5315   |
| 1.4253        | 10.0  | 12522  | 1.0634          | 0.5511   |
| 1.3888        | 11.0  | 13774  | 1.0489          | 0.5634   |
| 1.3681        | 12.0  | 15027  | 1.0663          | 0.5567   |
| 1.3802        | 13.0  | 16279  | 1.0304          | 0.5667   |
| 1.4016        | 14.0  | 17531  | 1.0592          | 0.5518   |
| 1.376         | 15.0  | 18783  | 1.0080          | 0.5776   |
| 1.3539        | 16.0  | 20036  | 1.0103          | 0.5742   |
| 1.3725        | 17.0  | 21288  | 1.0261          | 0.5636   |
| 1.3104        | 18.0  | 22540  | 1.0304          | 0.5686   |
| 1.3448        | 19.0  | 23792  | 1.0184          | 0.5687   |
| 1.3479        | 20.0  | 25045  | 0.9968          | 0.5809   |
| 1.3517        | 21.0  | 26297  | 1.1350          | 0.5182   |
| 1.3367        | 22.0  | 27549  | 0.9835          | 0.5867   |
| 1.3002        | 23.0  | 28801  | 1.0193          | 0.5736   |
| 1.3238        | 24.0  | 30054  | 0.9820          | 0.5875   |
| 1.2865        | 25.0  | 31306  | 1.0267          | 0.5617   |
| 1.3029        | 26.0  | 32558  | 1.0086          | 0.5730   |
| 1.3173        | 27.0  | 33810  | 0.9750          | 0.5924   |
| 1.297         | 28.0  | 35063  | 0.9851          | 0.5848   |
| 1.3105        | 29.0  | 36315  | 1.0306          | 0.5685   |
| 1.3477        | 30.0  | 37567  | 0.9977          | 0.5845   |
| 1.2565        | 31.0  | 38819  | 0.9900          | 0.5851   |
| 1.2657        | 32.0  | 40072  | 1.0137          | 0.5862   |
| 1.2911        | 33.0  | 41324  | 0.9947          | 0.5889   |
| 1.2539        | 34.0  | 42576  | 0.9821          | 0.5914   |
| 1.2441        | 35.0  | 43828  | 1.0296          | 0.5763   |
| 1.2176        | 36.0  | 45081  | 1.0350          | 0.5806   |
| 1.25          | 37.0  | 46333  | 1.0195          | 0.5779   |
| 1.2647        | 38.0  | 47585  | 1.0021          | 0.5903   |
| 1.2428        | 39.0  | 48837  | 1.0087          | 0.5892   |
| 1.2364        | 40.0  | 50090  | 1.0025          | 0.5947   |
| 1.2083        | 41.0  | 51342  | 1.0427          | 0.5862   |
| 1.2002        | 42.0  | 52594  | 1.0303          | 0.5878   |
| 1.2071        | 43.0  | 53846  | 1.0190          | 0.5909   |
| 1.1536        | 44.0  | 55099  | 1.0314          | 0.5920   |
| 1.2029        | 45.0  | 56351  | 1.0570          | 0.5839   |
| 1.2249        | 46.0  | 57603  | 1.0508          | 0.5828   |
| 1.1913        | 47.0  | 58855  | 1.0493          | 0.5853   |
| 1.1938        | 48.0  | 60108  | 1.0575          | 0.5857   |
| 1.1724        | 49.0  | 61360  | 1.0700          | 0.5905   |
| 1.1536        | 50.0  | 62612  | 1.0841          | 0.5853   |
| 1.1239        | 51.0  | 63864  | 1.0803          | 0.5865   |
| 1.1743        | 52.0  | 65117  | 1.0864          | 0.5880   |
| 1.1414        | 53.0  | 66369  | 1.1224          | 0.5819   |
| 1.1411        | 54.0  | 67621  | 1.1316          | 0.5780   |
| 1.1029        | 55.0  | 68873  | 1.1070          | 0.5860   |
| 1.1353        | 56.0  | 70126  | 1.1247          | 0.5847   |
| 1.1293        | 57.0  | 71378  | 1.1279          | 0.5805   |
| 1.1335        | 58.0  | 72630  | 1.1482          | 0.5812   |
| 1.1157        | 59.0  | 73882  | 1.1960          | 0.5674   |
| 1.0891        | 60.0  | 75135  | 1.1414          | 0.5848   |
| 1.1299        | 61.0  | 76387  | 1.1658          | 0.5790   |
| 1.0828        | 62.0  | 77639  | 1.1753          | 0.5806   |
| 1.0866        | 63.0  | 78891  | 1.1767          | 0.5755   |
| 1.0721        | 64.0  | 80144  | 1.1861          | 0.5808   |
| 1.0682        | 65.0  | 81396  | 1.2083          | 0.5749   |
| 1.0747        | 66.0  | 82648  | 1.2204          | 0.5755   |
| 1.0902        | 67.0  | 83900  | 1.2175          | 0.5750   |
| 1.0381        | 68.0  | 85153  | 1.2445          | 0.5738   |
| 1.049         | 69.0  | 86405  | 1.2674          | 0.5707   |
| 1.0501        | 70.0  | 87657  | 1.2602          | 0.5740   |
| 1.0117        | 71.0  | 88909  | 1.2549          | 0.5687   |
| 1.0179        | 72.0  | 90162  | 1.3010          | 0.5690   |
| 1.0788        | 73.0  | 91414  | 1.2723          | 0.5726   |
| 1.0234        | 74.0  | 92666  | 1.3162          | 0.5717   |
| 1.0325        | 75.0  | 93918  | 1.3136          | 0.5692   |
| 1.0079        | 76.0  | 95171  | 1.3337          | 0.5655   |
| 1.058         | 77.0  | 96423  | 1.3171          | 0.5719   |
| 0.9968        | 78.0  | 97675  | 1.3470          | 0.5693   |
| 1.0217        | 79.0  | 98927  | 1.3418          | 0.5733   |
| 1.0124        | 80.0  | 100180 | 1.3518          | 0.5700   |
| 0.9823        | 81.0  | 101432 | 1.3646          | 0.5700   |
| 0.9627        | 82.0  | 102684 | 1.3658          | 0.5686   |
| 0.9773        | 83.0  | 103936 | 1.3811          | 0.5674   |
| 0.9855        | 84.0  | 105189 | 1.4082          | 0.5638   |
| 0.9928        | 85.0  | 106441 | 1.3877          | 0.5612   |
| 1.0025        | 86.0  | 107693 | 1.3925          | 0.5653   |
| 0.9583        | 87.0  | 108945 | 1.4313          | 0.5625   |
| 0.977         | 88.0  | 110198 | 1.4153          | 0.5651   |
| 0.9825        | 89.0  | 111450 | 1.4426          | 0.5619   |
| 0.9315        | 90.0  | 112702 | 1.4376          | 0.5643   |
| 0.8916        | 91.0  | 113954 | 1.4630          | 0.5618   |
| 0.9495        | 92.0  | 115207 | 1.4501          | 0.5627   |
| 0.9372        | 93.0  | 116459 | 1.4606          | 0.5622   |
| 0.9284        | 94.0  | 117711 | 1.4725          | 0.5608   |
| 0.9266        | 95.0  | 118963 | 1.4680          | 0.5607   |
| 0.8858        | 96.0  | 120216 | 1.4705          | 0.5626   |
| 0.9025        | 97.0  | 121468 | 1.4818          | 0.5616   |
| 0.902         | 98.0  | 122720 | 1.4871          | 0.5606   |
| 0.8961        | 99.0  | 123972 | 1.4881          | 0.5612   |
| 0.9204        | 99.98 | 125200 | 1.4894          | 0.5609   |


### Framework versions

- Transformers 4.31.0
- Pytorch 2.0.1+cu117
- Datasets 2.17.0
- Tokenizers 0.13.3

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