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# vit-human-action-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 an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 7.1743
- Accuracy: 0.0663

## 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: 0.0002
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 1.1662        | 0.1269 | 100  | 3.2481          | 0.0435   |
| 1.1397        | 0.2538 | 200  | 3.6602          | 0.0807   |
| 0.8699        | 0.3807 | 300  | 4.1130          | 0.0365   |
| 0.8009        | 0.5076 | 400  | 3.8621          | 0.0720   |
| 0.8207        | 0.6345 | 500  | 4.1116          | 0.0704   |
| 0.7429        | 0.7614 | 600  | 4.2491          | 0.0641   |
| 0.7514        | 0.8883 | 700  | 4.5465          | 0.0654   |
| 0.4544        | 1.0152 | 800  | 4.5093          | 0.0778   |
| 0.3475        | 1.1421 | 900  | 4.8903          | 0.0763   |
| 0.3919        | 1.2690 | 1000 | 4.9154          | 0.0689   |
| 0.3912        | 1.3959 | 1100 | 5.3429          | 0.0687   |
| 0.3395        | 1.5228 | 1200 | 5.0278          | 0.0789   |
| 0.4903        | 1.6497 | 1300 | 5.7057          | 0.0533   |
| 0.4362        | 1.7766 | 1400 | 5.6518          | 0.0530   |
| 0.3901        | 1.9036 | 1500 | 5.5715          | 0.0737   |
| 0.1338        | 2.0305 | 1600 | 5.5777          | 0.0876   |
| 0.202         | 2.1574 | 1700 | 6.2254          | 0.0669   |
| 0.2534        | 2.2843 | 1800 | 6.5145          | 0.0559   |
| 0.2006        | 2.4112 | 1900 | 6.5269          | 0.0544   |
| 0.1209        | 2.5381 | 2000 | 6.1272          | 0.0719   |
| 0.1793        | 2.6650 | 2100 | 6.4983          | 0.0496   |
| 0.1034        | 2.7919 | 2200 | 6.2938          | 0.0611   |
| 0.0916        | 2.9188 | 2300 | 6.5665          | 0.0657   |
| 0.0538        | 3.0457 | 2400 | 6.7762          | 0.0659   |
| 0.0596        | 3.1726 | 2500 | 6.8592          | 0.0669   |
| 0.0114        | 3.2995 | 2600 | 7.0222          | 0.06     |
| 0.0708        | 3.4264 | 2700 | 7.1938          | 0.0552   |
| 0.0097        | 3.5533 | 2800 | 7.1244          | 0.0635   |
| 0.0371        | 3.6802 | 2900 | 7.1808          | 0.0633   |
| 0.0304        | 3.8071 | 3000 | 7.1658          | 0.0669   |
| 0.0065        | 3.9340 | 3100 | 7.1743          | 0.0663   |


### Framework versions

- Transformers 4.41.1
- Pytorch 2.3.0+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1

calling clapping running sitting sleeping texting using_laptop cycling dancing drinking eating fighting hugging laughing listening_to_music