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# Hierarchical_Agent_Action

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 agent_action_class dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5942
- Accuracy: 0.8403

## 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: 32
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 30
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.4407        | 0.81  | 100  | 2.2716          | 0.6058   |
| 1.7756        | 1.61  | 200  | 1.6162          | 0.7065   |
| 1.3948        | 2.42  | 300  | 1.2200          | 0.7698   |
| 1.131         | 3.23  | 400  | 1.0012          | 0.7856   |
| 0.9239        | 4.03  | 500  | 0.9055          | 0.7827   |
| 0.8699        | 4.84  | 600  | 0.8103          | 0.7827   |
| 0.6707        | 5.65  | 700  | 0.7610          | 0.7842   |
| 0.6206        | 6.45  | 800  | 0.7312          | 0.7885   |
| 0.5795        | 7.26  | 900  | 0.6989          | 0.8101   |
| 0.4914        | 8.06  | 1000 | 0.7066          | 0.7813   |
| 0.5087        | 8.87  | 1100 | 0.6398          | 0.8187   |
| 0.4373        | 9.68  | 1200 | 0.6293          | 0.8043   |
| 0.4365        | 10.48 | 1300 | 0.6726          | 0.7971   |
| 0.4517        | 11.29 | 1400 | 0.6047          | 0.8245   |
| 0.4114        | 12.1  | 1500 | 0.6088          | 0.8230   |
| 0.426         | 12.9  | 1600 | 0.6165          | 0.8201   |
| 0.3456        | 13.71 | 1700 | 0.6133          | 0.8259   |
| 0.332         | 14.52 | 1800 | 0.6736          | 0.8201   |
| 0.3646        | 15.32 | 1900 | 0.6406          | 0.8173   |
| 0.3287        | 16.13 | 2000 | 0.6978          | 0.7971   |
| 0.2793        | 16.94 | 2100 | 0.6433          | 0.8173   |
| 0.2924        | 17.74 | 2200 | 0.6474          | 0.8144   |
| 0.2605        | 18.55 | 2300 | 0.6279          | 0.8288   |
| 0.2016        | 19.35 | 2400 | 0.6361          | 0.8216   |
| 0.2524        | 20.16 | 2500 | 0.6394          | 0.8259   |
| 0.2017        | 20.97 | 2600 | 0.6683          | 0.8158   |
| 0.2082        | 21.77 | 2700 | 0.6389          | 0.8345   |
| 0.2751        | 22.58 | 2800 | 0.6141          | 0.8374   |
| 0.207         | 23.39 | 2900 | 0.6052          | 0.8259   |
| 0.1791        | 24.19 | 3000 | 0.6332          | 0.8230   |
| 0.1719        | 25.0  | 3100 | 0.5942          | 0.8403   |
| 0.1685        | 25.81 | 3200 | 0.6121          | 0.8360   |
| 0.1557        | 26.61 | 3300 | 0.6237          | 0.8345   |
| 0.1694        | 27.42 | 3400 | 0.6372          | 0.8317   |
| 0.1927        | 28.23 | 3500 | 0.6378          | 0.8273   |
| 0.1375        | 29.03 | 3600 | 0.6258          | 0.8331   |
| 0.1653        | 29.84 | 3700 | 0.6262          | 0.8331   |


### Framework versions

- Transformers 4.35.0
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.14.1

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