---
library_name: transformers
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: human_action_recognition_model
  results: []
---

<!-- 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. -->

# human_action_recognition_model

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: 7.8069
- Accuracy: 0.0659

## 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: 8
- 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

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 1.3102        | 0.3175 | 500  | 3.5439          | 0.0761   |
| 0.9861        | 0.6349 | 1000 | 4.1324          | 0.065    |
| 0.8791        | 0.9524 | 1500 | 4.6708          | 0.0752   |
| 0.5281        | 1.2698 | 2000 | 5.0605          | 0.0980   |
| 0.4598        | 1.5873 | 2500 | 6.1627          | 0.0437   |
| 0.4733        | 1.9048 | 3000 | 5.6746          | 0.0754   |
| 0.2844        | 2.2222 | 3500 | 6.5390          | 0.0746   |
| 0.1697        | 2.5397 | 4000 | 6.9396          | 0.0537   |
| 0.1697        | 2.8571 | 4500 | 7.1644          | 0.0672   |
| 0.1013        | 3.1746 | 5000 | 7.4083          | 0.0619   |
| 0.0556        | 3.4921 | 5500 | 7.4283          | 0.0694   |
| 0.0338        | 3.8095 | 6000 | 7.8069          | 0.0659   |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 3.0.0
- Tokenizers 0.19.1