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# square_run_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: 1.4067
- F1 Macro: 0.4365
- F1 Micro: 0.5152
- F1 Weighted: 0.4956
- Precision Macro: 0.4384
- Precision Micro: 0.5152
- Precision Weighted: 0.4986
- Recall Macro: 0.4561
- Recall Micro: 0.5152
- Recall Weighted: 0.5152
- Accuracy: 0.5152

## 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
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Use OptimizerNames.ADAMW_TORCH 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: 35

### 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:-----------:|:---------------:|:---------------:|:------------------:|:------------:|:------------:|:---------------:|:--------:|
| 1.8891        | 1.0   | 29   | 1.8671          | 0.1742   | 0.2576   | 0.2101      | 0.1681          | 0.2576          | 0.2045             | 0.2142       | 0.2576       | 0.2576          | 0.2576   |
| 1.8327        | 2.0   | 58   | 1.8124          | 0.1570   | 0.3182   | 0.1937      | 0.1335          | 0.3182          | 0.1611             | 0.2508       | 0.3182       | 0.3182          | 0.3182   |
| 1.9127        | 3.0   | 87   | 1.7830          | 0.2085   | 0.3182   | 0.2576      | 0.2128          | 0.3182          | 0.2618             | 0.2625       | 0.3182       | 0.3182          | 0.3182   |
| 1.4498        | 4.0   | 116  | 1.5796          | 0.2936   | 0.3864   | 0.3438      | 0.4342          | 0.3864          | 0.4527             | 0.3179       | 0.3864       | 0.3864          | 0.3864   |
| 1.2166        | 5.0   | 145  | 1.3485          | 0.3868   | 0.4773   | 0.4442      | 0.5068          | 0.4773          | 0.5373             | 0.4077       | 0.4773       | 0.4773          | 0.4773   |
| 1.5704        | 6.0   | 174  | 1.2560          | 0.4853   | 0.5606   | 0.5510      | 0.4906          | 0.5606          | 0.5679             | 0.5026       | 0.5606       | 0.5606          | 0.5606   |
| 1.2465        | 7.0   | 203  | 1.4968          | 0.3854   | 0.4924   | 0.4393      | 0.5611          | 0.4924          | 0.5975             | 0.4107       | 0.4924       | 0.4924          | 0.4924   |
| 1.2531        | 8.0   | 232  | 1.4663          | 0.4380   | 0.5      | 0.4841      | 0.4623          | 0.5             | 0.5302             | 0.4693       | 0.5          | 0.5             | 0.5      |
| 0.5318        | 9.0   | 261  | 1.1161          | 0.4938   | 0.5909   | 0.5646      | 0.4892          | 0.5909          | 0.5595             | 0.5176       | 0.5909       | 0.5909          | 0.5909   |
| 0.6824        | 10.0  | 290  | 1.1811          | 0.4802   | 0.5909   | 0.5515      | 0.4814          | 0.5909          | 0.5498             | 0.5148       | 0.5909       | 0.5909          | 0.5909   |
| 0.6324        | 11.0  | 319  | 1.2358          | 0.4927   | 0.5758   | 0.5506      | 0.5015          | 0.5758          | 0.5690             | 0.5226       | 0.5758       | 0.5758          | 0.5758   |
| 0.4145        | 12.0  | 348  | 1.1608          | 0.5846   | 0.6742   | 0.6643      | 0.5822          | 0.6742          | 0.6681             | 0.6005       | 0.6742       | 0.6742          | 0.6742   |
| 0.4805        | 13.0  | 377  | 1.3200          | 0.5276   | 0.5758   | 0.5689      | 0.5767          | 0.5758          | 0.6138             | 0.5269       | 0.5758       | 0.5758          | 0.5758   |
| 0.6232        | 14.0  | 406  | 1.3190          | 0.4790   | 0.5758   | 0.5517      | 0.5025          | 0.5758          | 0.5734             | 0.5006       | 0.5758       | 0.5758          | 0.5758   |
| 0.3475        | 15.0  | 435  | 1.1853          | 0.6303   | 0.6970   | 0.6894      | 0.6717          | 0.6970          | 0.7088             | 0.6312       | 0.6970       | 0.6970          | 0.6970   |
| 0.1956        | 16.0  | 464  | 1.5695          | 0.4323   | 0.5152   | 0.4974      | 0.4755          | 0.5152          | 0.5334             | 0.4358       | 0.5152       | 0.5152          | 0.5152   |
| 0.1519        | 17.0  | 493  | 1.4404          | 0.5819   | 0.6439   | 0.6317      | 0.6438          | 0.6439          | 0.6577             | 0.5706       | 0.6439       | 0.6439          | 0.6439   |
| 0.1031        | 18.0  | 522  | 1.4877          | 0.5370   | 0.6136   | 0.6041      | 0.5351          | 0.6136          | 0.5975             | 0.5422       | 0.6136       | 0.6136          | 0.6136   |
| 0.0615        | 19.0  | 551  | 1.4801          | 0.6013   | 0.6061   | 0.6106      | 0.6476          | 0.6061          | 0.6581             | 0.5951       | 0.6061       | 0.6061          | 0.6061   |
| 0.0249        | 20.0  | 580  | 1.6082          | 0.5198   | 0.5909   | 0.5825      | 0.5149          | 0.5909          | 0.5770             | 0.5272       | 0.5909       | 0.5909          | 0.5909   |
| 0.374         | 21.0  | 609  | 1.7594          | 0.6084   | 0.6288   | 0.6185      | 0.6712          | 0.6288          | 0.6679             | 0.6049       | 0.6288       | 0.6288          | 0.6288   |
| 0.025         | 22.0  | 638  | 1.4723          | 0.6446   | 0.6515   | 0.6520      | 0.6543          | 0.6515          | 0.6660             | 0.6479       | 0.6515       | 0.6515          | 0.6515   |
| 0.0096        | 23.0  | 667  | 1.5689          | 0.5899   | 0.6136   | 0.6089      | 0.6170          | 0.6136          | 0.6315             | 0.5878       | 0.6136       | 0.6136          | 0.6136   |
| 0.0661        | 24.0  | 696  | 1.6276          | 0.6056   | 0.6667   | 0.6576      | 0.6690          | 0.6667          | 0.6867             | 0.5949       | 0.6667       | 0.6667          | 0.6667   |
| 0.0463        | 25.0  | 725  | 1.6761          | 0.5591   | 0.6136   | 0.6085      | 0.6193          | 0.6136          | 0.6401             | 0.5521       | 0.6136       | 0.6136          | 0.6136   |
| 0.0118        | 26.0  | 754  | 1.6210          | 0.5353   | 0.6288   | 0.6075      | 0.5716          | 0.6288          | 0.6263             | 0.5410       | 0.6288       | 0.6288          | 0.6288   |
| 0.0018        | 27.0  | 783  | 1.6073          | 0.5860   | 0.6742   | 0.6575      | 0.5956          | 0.6742          | 0.6587             | 0.5929       | 0.6742       | 0.6742          | 0.6742   |
| 0.0336        | 28.0  | 812  | 1.5964          | 0.6086   | 0.6439   | 0.6411      | 0.6379          | 0.6439          | 0.6566             | 0.5979       | 0.6439       | 0.6439          | 0.6439   |
| 0.0014        | 29.0  | 841  | 1.5290          | 0.6873   | 0.7121   | 0.7083      | 0.7263          | 0.7121          | 0.7308             | 0.6734       | 0.7121       | 0.7121          | 0.7121   |
| 0.021         | 30.0  | 870  | 1.5440          | 0.6982   | 0.6970   | 0.6974      | 0.7076          | 0.6970          | 0.7170             | 0.7086       | 0.6970       | 0.6970          | 0.6970   |
| 0.0065        | 31.0  | 899  | 1.6576          | 0.6869   | 0.6970   | 0.6915      | 0.7430          | 0.6970          | 0.7270             | 0.6699       | 0.6970       | 0.6970          | 0.6970   |
| 0.0013        | 32.0  | 928  | 1.5603          | 0.7124   | 0.7197   | 0.7173      | 0.7508          | 0.7197          | 0.7411             | 0.6987       | 0.7197       | 0.7197          | 0.7197   |
| 0.0129        | 33.0  | 957  | 1.6028          | 0.6842   | 0.6894   | 0.6870      | 0.7153          | 0.6894          | 0.7059             | 0.6731       | 0.6894       | 0.6894          | 0.6894   |
| 0.0006        | 34.0  | 986  | 1.6075          | 0.6787   | 0.6818   | 0.6800      | 0.7094          | 0.6818          | 0.6991             | 0.6678       | 0.6818       | 0.6818          | 0.6818   |
| 0.0022        | 35.0  | 1015 | 1.6009          | 0.6848   | 0.6894   | 0.6869      | 0.7171          | 0.6894          | 0.7062             | 0.6731       | 0.6894       | 0.6894          | 0.6894   |


### Framework versions

- Transformers 4.48.2
- Pytorch 2.6.0+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0

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