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# square_run_second_vote_full_pic_50_age_gender

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: 1.6845
- F1 Macro: 0.2886
- F1 Micro: 0.3182
- F1 Weighted: 0.3108
- Precision Macro: 0.3139
- Precision Micro: 0.3182
- Precision Weighted: 0.3485
- Recall Macro: 0.3032
- Recall Micro: 0.3182
- Recall Weighted: 0.3182
- Accuracy: 0.3182

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:-----------:|:---------------:|:---------------:|:------------------:|:------------:|:------------:|:---------------:|:--------:|
| 1.8934        | 1.0   | 58   | 1.8939          | 0.0919   | 0.1970   | 0.1321      | 0.0799          | 0.1970          | 0.1097             | 0.1331       | 0.1970       | 0.1970          | 0.1970   |
| 1.851         | 2.0   | 116  | 2.0049          | 0.1066   | 0.1818   | 0.1280      | 0.1010          | 0.1818          | 0.1322             | 0.1720       | 0.1818       | 0.1818          | 0.1818   |
| 1.6292        | 3.0   | 174  | 1.8533          | 0.0849   | 0.2197   | 0.1086      | 0.0673          | 0.2197          | 0.0808             | 0.1568       | 0.2197       | 0.2197          | 0.2197   |
| 1.7267        | 4.0   | 232  | 1.8215          | 0.1715   | 0.2803   | 0.2141      | 0.3136          | 0.2803          | 0.3357             | 0.2133       | 0.2803       | 0.2803          | 0.2803   |
| 1.7363        | 5.0   | 290  | 1.8649          | 0.1065   | 0.1894   | 0.1268      | 0.1423          | 0.1894          | 0.1728             | 0.1730       | 0.1894       | 0.1894          | 0.1894   |
| 1.5974        | 6.0   | 348  | 1.8716          | 0.0916   | 0.25     | 0.1212      | 0.0721          | 0.25            | 0.0900             | 0.1746       | 0.25         | 0.25            | 0.25     |
| 1.8537        | 7.0   | 406  | 1.7017          | 0.2792   | 0.3333   | 0.3191      | 0.3181          | 0.3333          | 0.3633             | 0.2977       | 0.3333       | 0.3333          | 0.3333   |
| 1.4206        | 8.0   | 464  | 1.7872          | 0.1898   | 0.2727   | 0.2361      | 0.2092          | 0.2727          | 0.2442             | 0.2089       | 0.2727       | 0.2727          | 0.2727   |
| 2.1512        | 9.0   | 522  | 1.7402          | 0.2806   | 0.3333   | 0.3177      | 0.3019          | 0.3333          | 0.3379             | 0.2985       | 0.3333       | 0.3333          | 0.3333   |
| 1.6426        | 10.0  | 580  | 1.7943          | 0.2511   | 0.3106   | 0.2867      | 0.2731          | 0.3106          | 0.3042             | 0.2713       | 0.3106       | 0.3106          | 0.3106   |
| 1.5341        | 11.0  | 638  | 1.8591          | 0.2551   | 0.3030   | 0.2945      | 0.2564          | 0.3030          | 0.2941             | 0.2623       | 0.3030       | 0.3030          | 0.3030   |
| 1.0766        | 12.0  | 696  | 1.9545          | 0.2281   | 0.2955   | 0.2800      | 0.2455          | 0.2955          | 0.2902             | 0.2341       | 0.2955       | 0.2955          | 0.2955   |
| 0.8697        | 13.0  | 754  | 2.3504          | 0.1614   | 0.2727   | 0.2089      | 0.1739          | 0.2727          | 0.2207             | 0.2027       | 0.2727       | 0.2727          | 0.2727   |
| 0.7089        | 14.0  | 812  | 1.9392          | 0.2557   | 0.3409   | 0.3160      | 0.2531          | 0.3409          | 0.3054             | 0.2705       | 0.3409       | 0.3409          | 0.3409   |
| 0.9405        | 15.0  | 870  | 2.1086          | 0.2788   | 0.3485   | 0.3362      | 0.2945          | 0.3485          | 0.3480             | 0.2866       | 0.3485       | 0.3485          | 0.3485   |
| 0.768         | 16.0  | 928  | 2.1161          | 0.2990   | 0.3636   | 0.3599      | 0.3112          | 0.3636          | 0.3779             | 0.3073       | 0.3636       | 0.3636          | 0.3636   |
| 0.5405        | 17.0  | 986  | 2.2513          | 0.2757   | 0.3258   | 0.3197      | 0.2851          | 0.3258          | 0.3370             | 0.2867       | 0.3258       | 0.3258          | 0.3258   |
| 0.6639        | 18.0  | 1044 | 2.4633          | 0.2542   | 0.3106   | 0.3033      | 0.2616          | 0.3106          | 0.3156             | 0.2668       | 0.3106       | 0.3106          | 0.3106   |
| 0.1962        | 19.0  | 1102 | 2.5737          | 0.2463   | 0.3258   | 0.2995      | 0.2654          | 0.3258          | 0.3085             | 0.2575       | 0.3258       | 0.3258          | 0.3258   |
| 0.2221        | 20.0  | 1160 | 2.7099          | 0.2449   | 0.2803   | 0.2825      | 0.2577          | 0.2803          | 0.3097             | 0.2521       | 0.2803       | 0.2803          | 0.2803   |
| 0.3077        | 21.0  | 1218 | 2.7888          | 0.2527   | 0.3106   | 0.2980      | 0.2673          | 0.3106          | 0.3100             | 0.2626       | 0.3106       | 0.3106          | 0.3106   |
| 0.1271        | 22.0  | 1276 | 2.9443          | 0.2291   | 0.2652   | 0.2661      | 0.2315          | 0.2652          | 0.2727             | 0.2319       | 0.2652       | 0.2652          | 0.2652   |
| 0.1309        | 23.0  | 1334 | 3.0628          | 0.2714   | 0.3409   | 0.3305      | 0.3025          | 0.3409          | 0.3511             | 0.2700       | 0.3409       | 0.3409          | 0.3409   |
| 0.2454        | 24.0  | 1392 | 3.1552          | 0.2497   | 0.3182   | 0.3009      | 0.2573          | 0.3182          | 0.3021             | 0.2578       | 0.3182       | 0.3182          | 0.3182   |
| 0.0606        | 25.0  | 1450 | 3.2449          | 0.2319   | 0.2879   | 0.2810      | 0.2294          | 0.2879          | 0.2790             | 0.2379       | 0.2879       | 0.2879          | 0.2879   |
| 0.0862        | 26.0  | 1508 | 3.2262          | 0.2554   | 0.3182   | 0.3119      | 0.2557          | 0.3182          | 0.3114             | 0.2608       | 0.3182       | 0.3182          | 0.3182   |
| 0.0062        | 27.0  | 1566 | 3.2928          | 0.2711   | 0.3258   | 0.3251      | 0.2740          | 0.3258          | 0.3278             | 0.2719       | 0.3258       | 0.3258          | 0.3258   |
| 0.0427        | 28.0  | 1624 | 3.3795          | 0.2599   | 0.3182   | 0.3121      | 0.2595          | 0.3182          | 0.3101             | 0.2644       | 0.3182       | 0.3182          | 0.3182   |
| 0.007         | 29.0  | 1682 | 3.3703          | 0.2412   | 0.2955   | 0.2917      | 0.2459          | 0.2955          | 0.2940             | 0.2427       | 0.2955       | 0.2955          | 0.2955   |
| 0.0051        | 30.0  | 1740 | 3.4040          | 0.2484   | 0.3030   | 0.3003      | 0.2530          | 0.3030          | 0.3037             | 0.2500       | 0.3030       | 0.3030          | 0.3030   |


### Framework versions

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

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