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# square_run_square_run_first_vote_full_pic_25

This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.8536
- F1 Macro: 0.0897
- F1 Micro: 0.2273
- F1 Weighted: 0.1159
- Precision Macro: 0.1014
- Precision Micro: 0.2273
- Precision Weighted: 0.1202
- Recall Macro: 0.1612
- Recall Micro: 0.2273
- Recall Weighted: 0.2273
- Accuracy: 0.2273

## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 30

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1 Macro | F1 Micro | F1 Weighted | Precision Macro | Precision Micro | Precision Weighted | Recall Macro | Recall Micro | Recall Weighted | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:-----------:|:---------------:|:---------------:|:------------------:|:------------:|:------------:|:---------------:|:--------:|
| 2.0541        | 1.0   | 58   | 1.9294          | 0.0745   | 0.1742   | 0.0883      | 0.0677          | 0.1742          | 0.0775             | 0.1392       | 0.1742       | 0.1742          | 0.1742   |
| 1.899         | 2.0   | 116  | 2.0056          | 0.0914   | 0.1667   | 0.1071      | 0.1733          | 0.1667          | 0.2233             | 0.1507       | 0.1667       | 0.1667          | 0.1667   |
| 1.8937        | 3.0   | 174  | 1.8754          | 0.0736   | 0.2197   | 0.0978      | 0.1254          | 0.2197          | 0.1492             | 0.1565       | 0.2197       | 0.2197          | 0.2197   |
| 1.6804        | 4.0   | 232  | 1.8873          | 0.1517   | 0.2424   | 0.1844      | 0.1762          | 0.2424          | 0.2120             | 0.1913       | 0.2424       | 0.2424          | 0.2424   |
| 1.9232        | 5.0   | 290  | 1.8961          | 0.1135   | 0.2197   | 0.1375      | 0.1588          | 0.2197          | 0.1867             | 0.1798       | 0.2197       | 0.2197          | 0.2197   |
| 1.9641        | 6.0   | 348  | 1.8811          | 0.1590   | 0.2576   | 0.1993      | 0.1760          | 0.2576          | 0.2156             | 0.2014       | 0.2576       | 0.2576          | 0.2576   |
| 2.0347        | 7.0   | 406  | 1.9128          | 0.1464   | 0.25     | 0.1728      | 0.2850          | 0.25            | 0.3156             | 0.2085       | 0.25         | 0.25            | 0.25     |
| 1.6055        | 8.0   | 464  | 1.8785          | 0.0897   | 0.1894   | 0.1134      | 0.1093          | 0.1894          | 0.1335             | 0.1456       | 0.1894       | 0.1894          | 0.1894   |
| 1.7139        | 9.0   | 522  | 1.8898          | 0.1370   | 0.2273   | 0.1573      | 0.1198          | 0.2273          | 0.1335             | 0.1915       | 0.2273       | 0.2273          | 0.2273   |
| 1.6365        | 10.0  | 580  | 2.0175          | 0.1712   | 0.2197   | 0.1920      | 0.2880          | 0.2197          | 0.3202             | 0.2121       | 0.2197       | 0.2197          | 0.2197   |
| 1.8532        | 11.0  | 638  | 1.9556          | 0.1660   | 0.2273   | 0.1964      | 0.1554          | 0.2273          | 0.1836             | 0.1913       | 0.2273       | 0.2273          | 0.2273   |
| 1.2227        | 12.0  | 696  | 2.0035          | 0.2204   | 0.2576   | 0.2473      | 0.2152          | 0.2576          | 0.2460             | 0.2339       | 0.2576       | 0.2576          | 0.2576   |
| 1.6314        | 13.0  | 754  | 2.2851          | 0.1228   | 0.1515   | 0.1330      | 0.1522          | 0.1515          | 0.1744             | 0.1455       | 0.1515       | 0.1515          | 0.1515   |
| 1.4037        | 14.0  | 812  | 2.4487          | 0.2087   | 0.2045   | 0.2052      | 0.2603          | 0.2045          | 0.2314             | 0.1982       | 0.2045       | 0.2045          | 0.2045   |
| 1.1671        | 15.0  | 870  | 2.3369          | 0.2516   | 0.2576   | 0.2536      | 0.2666          | 0.2576          | 0.2603             | 0.2534       | 0.2576       | 0.2576          | 0.2576   |
| 1.2144        | 16.0  | 928  | 2.5458          | 0.2020   | 0.25     | 0.2314      | 0.2126          | 0.25            | 0.2378             | 0.2129       | 0.25         | 0.25            | 0.25     |
| 0.7161        | 17.0  | 986  | 2.8359          | 0.1935   | 0.2273   | 0.2223      | 0.2512          | 0.2273          | 0.2767             | 0.1989       | 0.2273       | 0.2273          | 0.2273   |
| 0.7918        | 18.0  | 1044 | 2.9960          | 0.1857   | 0.25     | 0.2207      | 0.2161          | 0.25            | 0.2431             | 0.2032       | 0.25         | 0.25            | 0.25     |
| 0.3944        | 19.0  | 1102 | 3.1088          | 0.2928   | 0.2955   | 0.2922      | 0.3139          | 0.2955          | 0.3033             | 0.2887       | 0.2955       | 0.2955          | 0.2955   |
| 0.1982        | 20.0  | 1160 | 3.2756          | 0.2663   | 0.2652   | 0.2559      | 0.2978          | 0.2652          | 0.2843             | 0.2714       | 0.2652       | 0.2652          | 0.2652   |
| 0.282         | 21.0  | 1218 | 3.3012          | 0.2658   | 0.2803   | 0.2746      | 0.2849          | 0.2803          | 0.2807             | 0.2630       | 0.2803       | 0.2803          | 0.2803   |
| 0.6119        | 22.0  | 1276 | 3.3820          | 0.2684   | 0.2879   | 0.2772      | 0.2949          | 0.2879          | 0.3025             | 0.2745       | 0.2879       | 0.2879          | 0.2879   |
| 0.0598        | 23.0  | 1334 | 3.4127          | 0.2546   | 0.2652   | 0.2601      | 0.2570          | 0.2652          | 0.2616             | 0.2602       | 0.2652       | 0.2652          | 0.2652   |
| 0.0219        | 24.0  | 1392 | 3.6584          | 0.2391   | 0.2576   | 0.2488      | 0.2711          | 0.2576          | 0.2541             | 0.2377       | 0.2576       | 0.2576          | 0.2576   |
| 0.2059        | 25.0  | 1450 | 3.6858          | 0.2517   | 0.2652   | 0.2600      | 0.2717          | 0.2652          | 0.2684             | 0.2488       | 0.2652       | 0.2652          | 0.2652   |
| 0.5641        | 26.0  | 1508 | 3.8254          | 0.2395   | 0.2576   | 0.2515      | 0.2455          | 0.2576          | 0.2537             | 0.2406       | 0.2576       | 0.2576          | 0.2576   |
| 0.3301        | 27.0  | 1566 | 3.9264          | 0.2529   | 0.2727   | 0.2655      | 0.2580          | 0.2727          | 0.2670             | 0.2550       | 0.2727       | 0.2727          | 0.2727   |
| 0.2333        | 28.0  | 1624 | 4.0348          | 0.2007   | 0.2197   | 0.2100      | 0.1977          | 0.2197          | 0.2053             | 0.2077       | 0.2197       | 0.2197          | 0.2197   |
| 0.1264        | 29.0  | 1682 | 4.0264          | 0.2224   | 0.2348   | 0.2295      | 0.2281          | 0.2348          | 0.2308             | 0.2225       | 0.2348       | 0.2348          | 0.2348   |
| 0.0029        | 30.0  | 1740 | 4.0181          | 0.2304   | 0.2424   | 0.2376      | 0.2351          | 0.2424          | 0.2380             | 0.2304       | 0.2424       | 0.2424          | 0.2424   |


### Framework versions

- Transformers 4.49.0
- Pytorch 2.6.0+cu124
- Datasets 3.3.1
- Tokenizers 0.21.0

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