
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# jaffe_crop_200_iter

This model is a fine-tuned version of [WinKawaks/vit-tiny-patch16-224](https://huggingface.co/WinKawaks/vit-tiny-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6110
- Accuracy: 0.8333

## 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: Use 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: 200

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 1    | 2.7256          | 0.1667   |
| No log        | 2.0   | 2    | 2.5775          | 0.1667   |
| No log        | 3.0   | 3    | 2.5633          | 0.1333   |
| No log        | 4.0   | 4    | 2.3386          | 0.1333   |
| No log        | 5.0   | 5    | 2.3028          | 0.1      |
| No log        | 6.0   | 6    | 2.1672          | 0.2333   |
| No log        | 7.0   | 7    | 2.1696          | 0.0333   |
| No log        | 8.0   | 8    | 2.0133          | 0.0667   |
| No log        | 9.0   | 9    | 2.0010          | 0.1      |
| 2.3074        | 10.0  | 10   | 1.9153          | 0.3333   |
| 2.3074        | 11.0  | 11   | 2.0177          | 0.3      |
| 2.3074        | 12.0  | 12   | 1.8241          | 0.3333   |
| 2.3074        | 13.0  | 13   | 1.7967          | 0.3      |
| 2.3074        | 14.0  | 14   | 1.7210          | 0.3333   |
| 2.3074        | 15.0  | 15   | 1.6551          | 0.3333   |
| 2.3074        | 16.0  | 16   | 1.5307          | 0.5333   |
| 2.3074        | 17.0  | 17   | 1.4263          | 0.4333   |
| 2.3074        | 18.0  | 18   | 1.4219          | 0.4333   |
| 2.3074        | 19.0  | 19   | 1.4402          | 0.4333   |
| 1.5864        | 20.0  | 20   | 1.3050          | 0.5      |
| 1.5864        | 21.0  | 21   | 1.4508          | 0.4      |
| 1.5864        | 22.0  | 22   | 1.3384          | 0.4667   |
| 1.5864        | 23.0  | 23   | 1.1632          | 0.6      |
| 1.5864        | 24.0  | 24   | 1.0711          | 0.6333   |
| 1.5864        | 25.0  | 25   | 1.1361          | 0.4667   |
| 1.5864        | 26.0  | 26   | 1.2230          | 0.5667   |
| 1.5864        | 27.0  | 27   | 1.0167          | 0.7      |
| 1.5864        | 28.0  | 28   | 0.8815          | 0.6667   |
| 1.5864        | 29.0  | 29   | 1.0191          | 0.6667   |
| 0.7909        | 30.0  | 30   | 0.9474          | 0.6667   |
| 0.7909        | 31.0  | 31   | 0.9328          | 0.5333   |
| 0.7909        | 32.0  | 32   | 0.9476          | 0.6      |
| 0.7909        | 33.0  | 33   | 0.7911          | 0.7      |
| 0.7909        | 34.0  | 34   | 0.7609          | 0.7333   |
| 0.7909        | 35.0  | 35   | 0.9489          | 0.6333   |
| 0.7909        | 36.0  | 36   | 0.7199          | 0.6667   |
| 0.7909        | 37.0  | 37   | 0.6195          | 0.7667   |
| 0.7909        | 38.0  | 38   | 0.7611          | 0.7333   |
| 0.7909        | 39.0  | 39   | 0.8063          | 0.7333   |
| 0.3677        | 40.0  | 40   | 0.8360          | 0.6667   |
| 0.3677        | 41.0  | 41   | 0.7250          | 0.7333   |
| 0.3677        | 42.0  | 42   | 0.6228          | 0.8333   |
| 0.3677        | 43.0  | 43   | 0.7757          | 0.7667   |
| 0.3677        | 44.0  | 44   | 0.6767          | 0.7667   |
| 0.3677        | 45.0  | 45   | 0.8128          | 0.6667   |
| 0.3677        | 46.0  | 46   | 0.8584          | 0.7333   |
| 0.3677        | 47.0  | 47   | 0.8866          | 0.6333   |
| 0.3677        | 48.0  | 48   | 0.5143          | 0.8      |
| 0.3677        | 49.0  | 49   | 0.7074          | 0.7      |
| 0.192         | 50.0  | 50   | 0.7536          | 0.7333   |
| 0.192         | 51.0  | 51   | 0.7113          | 0.7667   |
| 0.192         | 52.0  | 52   | 0.8321          | 0.7      |
| 0.192         | 53.0  | 53   | 0.7229          | 0.7333   |
| 0.192         | 54.0  | 54   | 0.8839          | 0.7      |
| 0.192         | 55.0  | 55   | 0.5496          | 0.8      |
| 0.192         | 56.0  | 56   | 0.6769          | 0.8      |
| 0.192         | 57.0  | 57   | 0.5740          | 0.8333   |
| 0.192         | 58.0  | 58   | 0.6321          | 0.7667   |
| 0.192         | 59.0  | 59   | 0.7635          | 0.7667   |
| 0.1225        | 60.0  | 60   | 0.6869          | 0.8      |
| 0.1225        | 61.0  | 61   | 0.6595          | 0.8333   |
| 0.1225        | 62.0  | 62   | 0.5097          | 0.8      |
| 0.1225        | 63.0  | 63   | 0.5642          | 0.8333   |
| 0.1225        | 64.0  | 64   | 0.6503          | 0.8      |
| 0.1225        | 65.0  | 65   | 0.6877          | 0.7667   |
| 0.1225        | 66.0  | 66   | 0.6811          | 0.7333   |
| 0.1225        | 67.0  | 67   | 0.7854          | 0.7      |
| 0.1225        | 68.0  | 68   | 0.6378          | 0.8      |
| 0.1225        | 69.0  | 69   | 0.5148          | 0.8667   |
| 0.088         | 70.0  | 70   | 0.6571          | 0.8      |
| 0.088         | 71.0  | 71   | 0.7112          | 0.7333   |
| 0.088         | 72.0  | 72   | 0.6602          | 0.7333   |
| 0.088         | 73.0  | 73   | 0.4259          | 0.9      |
| 0.088         | 74.0  | 74   | 0.3600          | 0.8667   |
| 0.088         | 75.0  | 75   | 0.5726          | 0.8667   |
| 0.088         | 76.0  | 76   | 0.6638          | 0.7667   |
| 0.088         | 77.0  | 77   | 0.4641          | 0.8667   |
| 0.088         | 78.0  | 78   | 0.5186          | 0.8667   |
| 0.088         | 79.0  | 79   | 0.6024          | 0.8333   |
| 0.0581        | 80.0  | 80   | 0.4450          | 0.8667   |
| 0.0581        | 81.0  | 81   | 0.3267          | 0.9      |
| 0.0581        | 82.0  | 82   | 0.6442          | 0.8      |
| 0.0581        | 83.0  | 83   | 0.8130          | 0.8      |
| 0.0581        | 84.0  | 84   | 0.4391          | 0.8667   |
| 0.0581        | 85.0  | 85   | 0.5013          | 0.8333   |
| 0.0581        | 86.0  | 86   | 0.6059          | 0.8      |
| 0.0581        | 87.0  | 87   | 0.4916          | 0.8333   |
| 0.0581        | 88.0  | 88   | 0.4384          | 0.8667   |
| 0.0581        | 89.0  | 89   | 0.3366          | 0.9      |
| 0.0359        | 90.0  | 90   | 0.6082          | 0.7667   |
| 0.0359        | 91.0  | 91   | 0.2967          | 0.8333   |
| 0.0359        | 92.0  | 92   | 0.3954          | 0.9      |
| 0.0359        | 93.0  | 93   | 0.5354          | 0.8333   |
| 0.0359        | 94.0  | 94   | 0.4755          | 0.8667   |
| 0.0359        | 95.0  | 95   | 0.5060          | 0.8      |
| 0.0359        | 96.0  | 96   | 0.3716          | 0.8333   |
| 0.0359        | 97.0  | 97   | 0.3547          | 0.8333   |
| 0.0359        | 98.0  | 98   | 0.6991          | 0.8333   |
| 0.0359        | 99.0  | 99   | 0.4895          | 0.8333   |
| 0.0251        | 100.0 | 100  | 0.5676          | 0.8      |
| 0.0251        | 101.0 | 101  | 0.3866          | 0.8667   |
| 0.0251        | 102.0 | 102  | 0.7054          | 0.7667   |
| 0.0251        | 103.0 | 103  | 0.5586          | 0.8667   |
| 0.0251        | 104.0 | 104  | 0.5839          | 0.8333   |
| 0.0251        | 105.0 | 105  | 0.5091          | 0.8333   |
| 0.0251        | 106.0 | 106  | 0.5459          | 0.9      |
| 0.0251        | 107.0 | 107  | 0.4228          | 0.9      |
| 0.0251        | 108.0 | 108  | 0.4447          | 0.9      |
| 0.0251        | 109.0 | 109  | 0.5052          | 0.8667   |
| 0.023         | 110.0 | 110  | 0.5494          | 0.8      |
| 0.023         | 111.0 | 111  | 0.6297          | 0.8333   |
| 0.023         | 112.0 | 112  | 0.6272          | 0.8667   |
| 0.023         | 113.0 | 113  | 0.6439          | 0.8333   |
| 0.023         | 114.0 | 114  | 0.3996          | 0.8667   |
| 0.023         | 115.0 | 115  | 0.4805          | 0.8333   |
| 0.023         | 116.0 | 116  | 0.4350          | 0.9      |
| 0.023         | 117.0 | 117  | 0.7719          | 0.8      |
| 0.023         | 118.0 | 118  | 0.5710          | 0.8333   |
| 0.023         | 119.0 | 119  | 0.3579          | 0.9      |
| 0.0292        | 120.0 | 120  | 0.3309          | 0.9333   |
| 0.0292        | 121.0 | 121  | 0.2649          | 0.9333   |
| 0.0292        | 122.0 | 122  | 0.3858          | 0.8333   |
| 0.0292        | 123.0 | 123  | 0.6109          | 0.8      |
| 0.0292        | 124.0 | 124  | 0.4734          | 0.8      |
| 0.0292        | 125.0 | 125  | 0.5604          | 0.8333   |
| 0.0292        | 126.0 | 126  | 0.3509          | 0.8667   |
| 0.0292        | 127.0 | 127  | 0.4752          | 0.9      |
| 0.0292        | 128.0 | 128  | 0.2966          | 0.8667   |
| 0.0292        | 129.0 | 129  | 0.5186          | 0.8667   |
| 0.0155        | 130.0 | 130  | 0.4547          | 0.8667   |
| 0.0155        | 131.0 | 131  | 0.3391          | 0.9      |
| 0.0155        | 132.0 | 132  | 0.4527          | 0.8667   |
| 0.0155        | 133.0 | 133  | 0.4476          | 0.8667   |
| 0.0155        | 134.0 | 134  | 0.5800          | 0.8667   |
| 0.0155        | 135.0 | 135  | 0.4653          | 0.8667   |
| 0.0155        | 136.0 | 136  | 0.3927          | 0.9      |
| 0.0155        | 137.0 | 137  | 0.4538          | 0.8333   |
| 0.0155        | 138.0 | 138  | 0.3952          | 0.9      |
| 0.0155        | 139.0 | 139  | 0.3949          | 0.9333   |
| 0.0112        | 140.0 | 140  | 0.5354          | 0.9      |
| 0.0112        | 141.0 | 141  | 0.5307          | 0.8333   |
| 0.0112        | 142.0 | 142  | 0.4757          | 0.9      |
| 0.0112        | 143.0 | 143  | 0.4342          | 0.9      |
| 0.0112        | 144.0 | 144  | 0.3978          | 0.9      |
| 0.0112        | 145.0 | 145  | 0.5695          | 0.8333   |
| 0.0112        | 146.0 | 146  | 0.5495          | 0.8      |
| 0.0112        | 147.0 | 147  | 0.4235          | 0.8667   |
| 0.0112        | 148.0 | 148  | 0.3878          | 0.9      |
| 0.0112        | 149.0 | 149  | 0.5536          | 0.9      |
| 0.0066        | 150.0 | 150  | 0.4343          | 0.8333   |
| 0.0066        | 151.0 | 151  | 0.5915          | 0.8667   |
| 0.0066        | 152.0 | 152  | 0.6523          | 0.8      |
| 0.0066        | 153.0 | 153  | 0.6478          | 0.8333   |
| 0.0066        | 154.0 | 154  | 0.6078          | 0.8333   |
| 0.0066        | 155.0 | 155  | 0.5253          | 0.9      |
| 0.0066        | 156.0 | 156  | 0.5023          | 0.9      |
| 0.0066        | 157.0 | 157  | 0.6782          | 0.8667   |
| 0.0066        | 158.0 | 158  | 0.4155          | 0.9      |
| 0.0066        | 159.0 | 159  | 0.6239          | 0.8667   |
| 0.0063        | 160.0 | 160  | 0.4657          | 0.8667   |
| 0.0063        | 161.0 | 161  | 0.3858          | 0.9      |
| 0.0063        | 162.0 | 162  | 0.4525          | 0.8667   |
| 0.0063        | 163.0 | 163  | 0.2853          | 0.9      |
| 0.0063        | 164.0 | 164  | 0.3835          | 0.8667   |
| 0.0063        | 165.0 | 165  | 0.3866          | 0.8333   |
| 0.0063        | 166.0 | 166  | 0.5272          | 0.8      |
| 0.0063        | 167.0 | 167  | 0.5175          | 0.8667   |
| 0.0063        | 168.0 | 168  | 0.5153          | 0.9      |
| 0.0063        | 169.0 | 169  | 0.4730          | 0.8667   |
| 0.0048        | 170.0 | 170  | 0.6657          | 0.8333   |
| 0.0048        | 171.0 | 171  | 0.5745          | 0.9      |
| 0.0048        | 172.0 | 172  | 0.7296          | 0.8      |
| 0.0048        | 173.0 | 173  | 0.4948          | 0.8333   |
| 0.0048        | 174.0 | 174  | 0.4577          | 0.8667   |
| 0.0048        | 175.0 | 175  | 0.5703          | 0.8667   |
| 0.0048        | 176.0 | 176  | 0.7392          | 0.8333   |
| 0.0048        | 177.0 | 177  | 0.7239          | 0.9      |
| 0.0048        | 178.0 | 178  | 0.3202          | 0.9      |
| 0.0048        | 179.0 | 179  | 0.4292          | 0.9      |
| 0.003         | 180.0 | 180  | 0.6611          | 0.8333   |
| 0.003         | 181.0 | 181  | 0.4829          | 0.9      |
| 0.003         | 182.0 | 182  | 0.4959          | 0.8667   |
| 0.003         | 183.0 | 183  | 0.2886          | 0.9      |
| 0.003         | 184.0 | 184  | 0.6587          | 0.8667   |
| 0.003         | 185.0 | 185  | 0.7223          | 0.8      |
| 0.003         | 186.0 | 186  | 0.6374          | 0.8667   |
| 0.003         | 187.0 | 187  | 0.5756          | 0.8333   |
| 0.003         | 188.0 | 188  | 0.6505          | 0.8667   |
| 0.003         | 189.0 | 189  | 0.5517          | 0.8667   |
| 0.0025        | 190.0 | 190  | 0.5176          | 0.8667   |
| 0.0025        | 191.0 | 191  | 0.4003          | 0.9      |
| 0.0025        | 192.0 | 192  | 0.5594          | 0.8667   |
| 0.0025        | 193.0 | 193  | 0.4229          | 0.9      |
| 0.0025        | 194.0 | 194  | 0.5938          | 0.8667   |
| 0.0025        | 195.0 | 195  | 0.6415          | 0.8667   |
| 0.0025        | 196.0 | 196  | 0.5056          | 0.8667   |
| 0.0025        | 197.0 | 197  | 0.5146          | 0.9      |
| 0.0025        | 198.0 | 198  | 0.5822          | 0.8667   |
| 0.0025        | 199.0 | 199  | 0.6066          | 0.8667   |
| 0.0021        | 200.0 | 200  | 0.6110          | 0.8333   |


### Framework versions

- Transformers 4.47.0
- Pytorch 2.5.1+cu121
- Datasets 3.3.1
- Tokenizers 0.21.0

an di fe ha ne sa su