---
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: activity_classification
  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. -->

# activity_classification

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: 0.7631
- Accuracy: 0.7710

## 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: 3e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 30

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.1235        | 1.0   | 315  | 1.3182          | 0.7099   |
| 1.0404        | 2.0   | 630  | 0.9831          | 0.7278   |
| 0.7899        | 3.0   | 945  | 0.9509          | 0.7175   |
| 0.6961        | 4.0   | 1260 | 0.8258          | 0.7460   |
| 0.615         | 5.0   | 1575 | 0.7890          | 0.7667   |
| 0.5534        | 6.0   | 1890 | 0.7876          | 0.7591   |
| 0.524         | 7.0   | 2205 | 0.7627          | 0.7663   |
| 0.4588        | 8.0   | 2520 | 0.8256          | 0.7468   |
| 0.4407        | 9.0   | 2835 | 0.8041          | 0.7615   |
| 0.4039        | 10.0  | 3150 | 0.8367          | 0.7540   |
| 0.3966        | 11.0  | 3465 | 0.8708          | 0.7492   |
| 0.366         | 12.0  | 3780 | 0.8410          | 0.7544   |
| 0.3522        | 13.0  | 4095 | 0.9019          | 0.7365   |
| 0.3495        | 14.0  | 4410 | 0.8240          | 0.7567   |
| 0.3206        | 15.0  | 4725 | 0.8428          | 0.7607   |
| 0.3172        | 16.0  | 5040 | 0.8626          | 0.7607   |
| 0.2931        | 17.0  | 5355 | 1.0311          | 0.7306   |
| 0.2943        | 18.0  | 5670 | 0.9393          | 0.7544   |
| 0.2886        | 19.0  | 5985 | 0.9379          | 0.7472   |
| 0.2785        | 20.0  | 6300 | 0.8911          | 0.7552   |
| 0.274         | 21.0  | 6615 | 0.9730          | 0.7484   |
| 0.2716        | 22.0  | 6930 | 0.9546          | 0.7504   |
| 0.2686        | 23.0  | 7245 | 0.8939          | 0.7651   |
| 0.2489        | 24.0  | 7560 | 0.9397          | 0.7480   |
| 0.257         | 25.0  | 7875 | 0.9298          | 0.7552   |
| 0.244         | 26.0  | 8190 | 0.9977          | 0.7437   |
| 0.2333        | 27.0  | 8505 | 0.9967          | 0.75     |
| 0.2376        | 28.0  | 8820 | 1.0012          | 0.7508   |
| 0.2428        | 29.0  | 9135 | 0.9674          | 0.7421   |
| 0.224         | 30.0  | 9450 | 1.0239          | 0.7361   |


### Framework versions

- Transformers 4.33.3
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3