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# square_run_first_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: 1.6395
- F1 Macro: 0.2469
- F1 Micro: 0.3485
- F1 Weighted: 0.2801
- Precision Macro: 0.2428
- Precision Micro: 0.3485
- Precision Weighted: 0.2847
- Recall Macro: 0.3062
- Recall Micro: 0.3485
- Recall Weighted: 0.3485
- Accuracy: 0.3485

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:-----------:|:---------------:|:---------------:|:------------------:|:------------:|:------------:|:---------------:|:--------:|
| 1.952         | 1.0   | 58   | 1.9331          | 0.1015   | 0.1894   | 0.1193      | 0.0782          | 0.1894          | 0.0909             | 0.1571       | 0.1894       | 0.1894          | 0.1894   |
| 1.8507        | 2.0   | 116  | 1.9609          | 0.0434   | 0.1364   | 0.0478      | 0.0314          | 0.1364          | 0.0344             | 0.1228       | 0.1364       | 0.1364          | 0.1364   |
| 1.8752        | 3.0   | 174  | 1.8530          | 0.1515   | 0.2197   | 0.1864      | 0.1396          | 0.2197          | 0.1747             | 0.1834       | 0.2197       | 0.2197          | 0.2197   |
| 1.6369        | 4.0   | 232  | 1.8198          | 0.1627   | 0.2652   | 0.2010      | 0.2272          | 0.2652          | 0.2553             | 0.2011       | 0.2652       | 0.2652          | 0.2652   |
| 1.9706        | 5.0   | 290  | 1.7950          | 0.2160   | 0.2955   | 0.2460      | 0.2685          | 0.2955          | 0.3249             | 0.2686       | 0.2955       | 0.2955          | 0.2955   |
| 1.738         | 6.0   | 348  | 1.6951          | 0.3343   | 0.4091   | 0.3811      | 0.4054          | 0.4091          | 0.4381             | 0.3537       | 0.4091       | 0.4091          | 0.4091   |
| 1.924         | 7.0   | 406  | 1.6492          | 0.3123   | 0.3636   | 0.3150      | 0.5154          | 0.3636          | 0.4299             | 0.3365       | 0.3636       | 0.3636          | 0.3636   |
| 1.8234        | 8.0   | 464  | 1.7347          | 0.3183   | 0.3712   | 0.3515      | 0.3698          | 0.3712          | 0.4277             | 0.3554       | 0.3712       | 0.3712          | 0.3712   |
| 1.5916        | 9.0   | 522  | 1.8146          | 0.2720   | 0.3712   | 0.3008      | 0.3597          | 0.3712          | 0.3850             | 0.3281       | 0.3712       | 0.3712          | 0.3712   |
| 1.578         | 10.0  | 580  | 1.7509          | 0.2703   | 0.3561   | 0.3033      | 0.3571          | 0.3561          | 0.4226             | 0.3217       | 0.3561       | 0.3561          | 0.3561   |
| 1.5857        | 11.0  | 638  | 1.8672          | 0.3019   | 0.3561   | 0.3520      | 0.3399          | 0.3561          | 0.4037             | 0.3121       | 0.3561       | 0.3561          | 0.3561   |
| 1.1684        | 12.0  | 696  | 1.8947          | 0.2724   | 0.3258   | 0.3168      | 0.2707          | 0.3258          | 0.3138             | 0.2793       | 0.3258       | 0.3258          | 0.3258   |
| 1.3507        | 13.0  | 754  | 1.9123          | 0.3161   | 0.3636   | 0.3651      | 0.3271          | 0.3636          | 0.3832             | 0.3189       | 0.3636       | 0.3636          | 0.3636   |
| 1.1413        | 14.0  | 812  | 1.9088          | 0.3210   | 0.3788   | 0.3659      | 0.3221          | 0.3788          | 0.3622             | 0.3287       | 0.3788       | 0.3788          | 0.3788   |
| 1.2466        | 15.0  | 870  | 2.0905          | 0.3428   | 0.4015   | 0.3831      | 0.3574          | 0.4015          | 0.4108             | 0.3649       | 0.4015       | 0.4015          | 0.4015   |
| 1.2063        | 16.0  | 928  | 2.2063          | 0.3331   | 0.3864   | 0.3746      | 0.3376          | 0.3864          | 0.3775             | 0.3418       | 0.3864       | 0.3864          | 0.3864   |
| 0.25          | 17.0  | 986  | 2.1276          | 0.3909   | 0.4242   | 0.4287      | 0.4100          | 0.4242          | 0.4593             | 0.3942       | 0.4242       | 0.4242          | 0.4242   |
| 0.3857        | 18.0  | 1044 | 2.3733          | 0.3631   | 0.4242   | 0.4119      | 0.3618          | 0.4242          | 0.4050             | 0.3701       | 0.4242       | 0.4242          | 0.4242   |
| 0.0546        | 19.0  | 1102 | 2.4860          | 0.3277   | 0.3864   | 0.3769      | 0.3432          | 0.3864          | 0.3902             | 0.3345       | 0.3864       | 0.3864          | 0.3864   |
| 0.0621        | 20.0  | 1160 | 2.5209          | 0.3879   | 0.4242   | 0.4119      | 0.4393          | 0.4242          | 0.4335             | 0.3850       | 0.4242       | 0.4242          | 0.4242   |
| 0.1491        | 21.0  | 1218 | 2.7192          | 0.3713   | 0.4242   | 0.4142      | 0.3740          | 0.4242          | 0.4124             | 0.3777       | 0.4242       | 0.4242          | 0.4242   |
| 0.4118        | 22.0  | 1276 | 2.9182          | 0.3327   | 0.3864   | 0.3752      | 0.3317          | 0.3864          | 0.3734             | 0.3427       | 0.3864       | 0.3864          | 0.3864   |
| 0.1833        | 23.0  | 1334 | 2.9567          | 0.3204   | 0.3636   | 0.3580      | 0.3325          | 0.3636          | 0.3805             | 0.3318       | 0.3636       | 0.3636          | 0.3636   |
| 0.0022        | 24.0  | 1392 | 3.0022          | 0.3432   | 0.4015   | 0.3824      | 0.3452          | 0.4015          | 0.3877             | 0.3643       | 0.4015       | 0.4015          | 0.4015   |
| 0.2174        | 25.0  | 1450 | 3.0656          | 0.3537   | 0.3864   | 0.3803      | 0.3574          | 0.3864          | 0.3796             | 0.3568       | 0.3864       | 0.3864          | 0.3864   |
| 0.0191        | 26.0  | 1508 | 3.1698          | 0.3451   | 0.4091   | 0.3920      | 0.3502          | 0.4091          | 0.3992             | 0.3627       | 0.4091       | 0.4091          | 0.4091   |
| 0.0051        | 27.0  | 1566 | 3.3015          | 0.3389   | 0.4015   | 0.3816      | 0.3394          | 0.4015          | 0.3844             | 0.3566       | 0.4015       | 0.4015          | 0.4015   |
| 0.0205        | 28.0  | 1624 | 3.2677          | 0.3457   | 0.4091   | 0.3893      | 0.3422          | 0.4091          | 0.3864             | 0.3634       | 0.4091       | 0.4091          | 0.4091   |
| 0.0016        | 29.0  | 1682 | 3.1995          | 0.3385   | 0.3939   | 0.3810      | 0.3324          | 0.3939          | 0.3723             | 0.3479       | 0.3939       | 0.3939          | 0.3939   |
| 0.0011        | 30.0  | 1740 | 3.2359          | 0.3495   | 0.4091   | 0.3927      | 0.3409          | 0.4091          | 0.3823             | 0.3634       | 0.4091       | 0.4091          | 0.4091   |


### Framework versions

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

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