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# visual-emotion-recognition

This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1334
- Accuracy: 0.6375
- Precision: 0.6498
- Recall: 0.6375
- F1: 0.6341

## 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: 1e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 3
- total_train_batch_size: 48
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 100
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 2.0671        | 0.97  | 13   | 2.0660          | 0.125    | 0.2709    | 0.125  | 0.1135 |
| 2.0576        | 1.95  | 26   | 2.0563          | 0.1562   | 0.2932    | 0.1562 | 0.1402 |
| 2.044         | 3.0   | 40   | 2.0439          | 0.1875   | 0.2554    | 0.1875 | 0.1827 |
| 2.0209        | 3.98  | 53   | 2.0309          | 0.2062   | 0.2405    | 0.2062 | 0.1961 |
| 1.9938        | 4.95  | 66   | 2.0176          | 0.2188   | 0.2410    | 0.2188 | 0.2062 |
| 1.9894        | 6.0   | 80   | 1.9960          | 0.2625   | 0.2700    | 0.2625 | 0.2438 |
| 1.9667        | 6.97  | 93   | 1.9743          | 0.3125   | 0.3089    | 0.3125 | 0.2901 |
| 1.9158        | 7.95  | 106  | 1.9421          | 0.3063   | 0.2557    | 0.3063 | 0.2687 |
| 1.8834        | 9.0   | 120  | 1.9042          | 0.3375   | 0.4019    | 0.3375 | 0.2888 |
| 1.8461        | 9.97  | 133  | 1.8521          | 0.3625   | 0.4132    | 0.3625 | 0.3021 |
| 1.7917        | 10.95 | 146  | 1.8023          | 0.3688   | 0.4144    | 0.3688 | 0.3056 |
| 1.7685        | 12.0  | 160  | 1.7552          | 0.375    | 0.4062    | 0.375  | 0.2978 |
| 1.7072        | 12.97 | 173  | 1.7071          | 0.3875   | 0.4266    | 0.3875 | 0.3164 |
| 1.6926        | 13.95 | 186  | 1.6742          | 0.375    | 0.4056    | 0.375  | 0.2996 |
| 1.6084        | 15.0  | 200  | 1.6476          | 0.3937   | 0.4411    | 0.3937 | 0.3358 |
| 1.6264        | 15.97 | 213  | 1.6231          | 0.3812   | 0.4357    | 0.3812 | 0.3311 |
| 1.5531        | 16.95 | 226  | 1.6019          | 0.4125   | 0.4676    | 0.4125 | 0.3626 |
| 1.5804        | 18.0  | 240  | 1.5773          | 0.3937   | 0.4442    | 0.3937 | 0.3428 |
| 1.54          | 18.98 | 253  | 1.5606          | 0.4      | 0.4565    | 0.4    | 0.3527 |
| 1.5461        | 19.95 | 266  | 1.5464          | 0.4437   | 0.5084    | 0.4437 | 0.4028 |
| 1.4841        | 21.0  | 280  | 1.5323          | 0.4313   | 0.4950    | 0.4313 | 0.3881 |
| 1.4765        | 21.98 | 293  | 1.5121          | 0.4313   | 0.4884    | 0.4313 | 0.3822 |
| 1.4838        | 22.95 | 306  | 1.4978          | 0.4375   | 0.5138    | 0.4375 | 0.4012 |
| 1.4487        | 24.0  | 320  | 1.4791          | 0.4437   | 0.5059    | 0.4437 | 0.4001 |
| 1.4272        | 24.98 | 333  | 1.4617          | 0.4562   | 0.5304    | 0.4562 | 0.4180 |
| 1.3886        | 25.95 | 346  | 1.4488          | 0.4625   | 0.5418    | 0.4625 | 0.4303 |
| 1.4529        | 27.0  | 360  | 1.4436          | 0.45     | 0.5147    | 0.45   | 0.4035 |
| 1.3894        | 27.98 | 373  | 1.4267          | 0.4688   | 0.5488    | 0.4688 | 0.4355 |
| 1.3848        | 28.95 | 386  | 1.4153          | 0.4625   | 0.5337    | 0.4625 | 0.4264 |
| 1.3561        | 30.0  | 400  | 1.3993          | 0.4875   | 0.5521    | 0.4875 | 0.4554 |
| 1.3184        | 30.98 | 413  | 1.3852          | 0.4813   | 0.5526    | 0.4813 | 0.4470 |
| 1.282         | 31.95 | 426  | 1.3703          | 0.4813   | 0.5480    | 0.4813 | 0.4449 |
| 1.2988        | 33.0  | 440  | 1.3674          | 0.4688   | 0.5541    | 0.4688 | 0.4395 |
| 1.2507        | 33.98 | 453  | 1.3594          | 0.4688   | 0.5347    | 0.4688 | 0.4307 |
| 1.2446        | 34.95 | 466  | 1.3519          | 0.4813   | 0.5616    | 0.4813 | 0.4514 |
| 1.2877        | 36.0  | 480  | 1.3547          | 0.4875   | 0.5599    | 0.4875 | 0.4605 |
| 1.2237        | 36.98 | 493  | 1.3342          | 0.5      | 0.5744    | 0.5    | 0.4654 |
| 1.2416        | 37.95 | 506  | 1.3214          | 0.4813   | 0.5693    | 0.4813 | 0.4551 |
| 1.1786        | 39.0  | 520  | 1.3122          | 0.4875   | 0.5674    | 0.4875 | 0.4586 |
| 1.193         | 39.98 | 533  | 1.2989          | 0.5      | 0.5755    | 0.5    | 0.4774 |
| 1.148         | 40.95 | 546  | 1.2962          | 0.5125   | 0.5811    | 0.5125 | 0.4755 |
| 1.1904        | 42.0  | 560  | 1.2860          | 0.5188   | 0.5863    | 0.5188 | 0.4928 |
| 1.1311        | 42.98 | 573  | 1.2893          | 0.5312   | 0.5936    | 0.5312 | 0.5117 |
| 1.1396        | 43.95 | 586  | 1.2860          | 0.4938   | 0.5633    | 0.4938 | 0.4698 |
| 1.1235        | 45.0  | 600  | 1.2802          | 0.5      | 0.5725    | 0.5    | 0.4758 |
| 1.1638        | 45.98 | 613  | 1.2596          | 0.525    | 0.5909    | 0.525  | 0.5058 |
| 1.0777        | 46.95 | 626  | 1.2668          | 0.5188   | 0.5796    | 0.5188 | 0.4861 |
| 1.1136        | 48.0  | 640  | 1.2520          | 0.55     | 0.6100    | 0.55   | 0.5291 |
| 1.047         | 48.98 | 653  | 1.2437          | 0.5375   | 0.5963    | 0.5375 | 0.5279 |
| 1.1101        | 49.95 | 666  | 1.2527          | 0.55     | 0.6195    | 0.55   | 0.5279 |
| 1.0412        | 51.0  | 680  | 1.2455          | 0.525    | 0.5927    | 0.525  | 0.5156 |
| 1.041         | 51.98 | 693  | 1.2245          | 0.55     | 0.6073    | 0.55   | 0.5353 |
| 0.9906        | 52.95 | 706  | 1.2307          | 0.575    | 0.6420    | 0.575  | 0.5600 |
| 0.9863        | 54.0  | 720  | 1.2307          | 0.5563   | 0.6150    | 0.5563 | 0.5362 |
| 0.943         | 54.98 | 733  | 1.2270          | 0.55     | 0.6152    | 0.55   | 0.5302 |
| 0.9557        | 55.95 | 746  | 1.2063          | 0.5312   | 0.5964    | 0.5312 | 0.5239 |
| 0.9518        | 57.0  | 760  | 1.2122          | 0.55     | 0.6232    | 0.55   | 0.5433 |
| 0.9545        | 57.98 | 773  | 1.1955          | 0.575    | 0.6144    | 0.575  | 0.5563 |
| 0.9195        | 58.95 | 786  | 1.2139          | 0.5563   | 0.6052    | 0.5563 | 0.5459 |
| 0.9267        | 60.0  | 800  | 1.1907          | 0.5687   | 0.6052    | 0.5687 | 0.5595 |
| 0.9384        | 60.98 | 813  | 1.1899          | 0.575    | 0.6449    | 0.575  | 0.5650 |
| 0.8727        | 61.95 | 826  | 1.1854          | 0.5813   | 0.6312    | 0.5813 | 0.5651 |
| 0.8541        | 63.0  | 840  | 1.1957          | 0.575    | 0.6407    | 0.575  | 0.5632 |
| 0.8899        | 63.98 | 853  | 1.1604          | 0.575    | 0.6196    | 0.575  | 0.5694 |
| 0.9036        | 64.95 | 866  | 1.1859          | 0.5563   | 0.6310    | 0.5563 | 0.5306 |
| 0.8177        | 66.0  | 880  | 1.1498          | 0.6125   | 0.6316    | 0.6125 | 0.6116 |
| 0.7854        | 66.97 | 893  | 1.1842          | 0.5687   | 0.6142    | 0.5687 | 0.5582 |
| 0.8054        | 67.95 | 906  | 1.1695          | 0.5938   | 0.6275    | 0.5938 | 0.5830 |
| 0.8582        | 69.0  | 920  | 1.1882          | 0.5687   | 0.6057    | 0.5687 | 0.5495 |
| 0.7603        | 69.97 | 933  | 1.2067          | 0.55     | 0.6025    | 0.55   | 0.5348 |
| 0.763         | 70.95 | 946  | 1.1690          | 0.5625   | 0.6036    | 0.5625 | 0.5439 |
| 0.8261        | 72.0  | 960  | 1.1616          | 0.6062   | 0.6306    | 0.6062 | 0.6016 |
| 0.884         | 72.97 | 973  | 1.1952          | 0.5625   | 0.6082    | 0.5625 | 0.5436 |
| 0.7843        | 73.95 | 986  | 1.1583          | 0.5687   | 0.5953    | 0.5687 | 0.5633 |
| 0.801         | 75.0  | 1000 | 1.1547          | 0.575    | 0.6013    | 0.575  | 0.5745 |
| 0.7454        | 75.97 | 1013 | 1.1372          | 0.5875   | 0.6193    | 0.5875 | 0.5761 |
| 0.7325        | 76.95 | 1026 | 1.1696          | 0.5938   | 0.6351    | 0.5938 | 0.5919 |
| 0.7931        | 78.0  | 1040 | 1.1511          | 0.6062   | 0.6342    | 0.6062 | 0.6053 |
| 0.7487        | 78.97 | 1053 | 1.1655          | 0.5625   | 0.5898    | 0.5625 | 0.5496 |
| 0.7262        | 79.95 | 1066 | 1.1394          | 0.6125   | 0.6295    | 0.6125 | 0.6048 |
| 0.7669        | 81.0  | 1080 | 1.1748          | 0.575    | 0.5966    | 0.575  | 0.5697 |
| 0.7028        | 81.97 | 1093 | 1.1418          | 0.5875   | 0.6178    | 0.5875 | 0.5885 |
| 0.7749        | 82.95 | 1106 | 1.1736          | 0.55     | 0.5446    | 0.55   | 0.5255 |
| 0.7233        | 84.0  | 1120 | 1.1645          | 0.5813   | 0.5973    | 0.5813 | 0.5699 |
| 0.5915        | 84.97 | 1133 | 1.1376          | 0.5875   | 0.6167    | 0.5875 | 0.5867 |
| 0.6985        | 85.95 | 1146 | 1.1665          | 0.5687   | 0.5868    | 0.5687 | 0.5533 |
| 0.6572        | 87.0  | 1160 | 1.1341          | 0.6      | 0.6245    | 0.6    | 0.5963 |
| 0.6317        | 87.97 | 1173 | 1.1327          | 0.6125   | 0.6288    | 0.6125 | 0.6026 |
| 0.6546        | 88.95 | 1186 | 1.1668          | 0.5687   | 0.5797    | 0.5687 | 0.5528 |
| 0.5801        | 90.0  | 1200 | 1.1521          | 0.5875   | 0.6161    | 0.5875 | 0.5818 |
| 0.6958        | 90.97 | 1213 | 1.1401          | 0.5875   | 0.6083    | 0.5875 | 0.5774 |
| 0.5856        | 91.95 | 1226 | 1.1379          | 0.5875   | 0.5888    | 0.5875 | 0.5760 |
| 0.6281        | 93.0  | 1240 | 1.1379          | 0.6125   | 0.6429    | 0.6125 | 0.6123 |
| 0.6518        | 93.97 | 1253 | 1.1619          | 0.6312   | 0.6547    | 0.6312 | 0.6247 |
| 0.6055        | 94.95 | 1266 | 1.1700          | 0.575    | 0.5962    | 0.575  | 0.5673 |
| 0.6181        | 96.0  | 1280 | 1.1550          | 0.5938   | 0.6281    | 0.5938 | 0.5970 |
| 0.6601        | 96.97 | 1293 | 1.1334          | 0.6375   | 0.6498    | 0.6375 | 0.6341 |
| 0.6112        | 97.5  | 1300 | 1.1007          | 0.6188   | 0.6341    | 0.6188 | 0.6207 |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.1

anger contempt disgust fear happy neutral sad surprise