---
license: apache-2.0
base_model: google/vit-base-patch16-224-in21K
tags:
- image-classification
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: Human_action_classifier
  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_classifier

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: 0.5303
- Accuracy: 0.8496

## 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: 7
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.4545        | 0.16  | 100  | 1.3145          | 0.6706   |
| 1.2568        | 0.32  | 200  | 1.0387          | 0.7179   |
| 1.3145        | 0.48  | 300  | 1.0027          | 0.7135   |
| 1.0866        | 0.63  | 400  | 0.8883          | 0.7377   |
| 1.0036        | 0.79  | 500  | 0.8973          | 0.7321   |
| 1.1811        | 0.95  | 600  | 0.8048          | 0.7571   |
| 0.9242        | 1.11  | 700  | 0.9095          | 0.7274   |
| 0.9477        | 1.27  | 800  | 0.8037          | 0.7619   |
| 0.8634        | 1.43  | 900  | 0.7938          | 0.7643   |
| 1.0098        | 1.59  | 1000 | 0.7328          | 0.7766   |
| 0.8176        | 1.75  | 1100 | 0.8065          | 0.7516   |
| 0.8072        | 1.9   | 1200 | 0.7768          | 0.7694   |
| 0.7739        | 2.06  | 1300 | 0.7624          | 0.7726   |
| 0.6851        | 2.22  | 1400 | 0.6687          | 0.7940   |
| 0.7496        | 2.38  | 1500 | 0.6806          | 0.7948   |
| 0.7352        | 2.54  | 1600 | 0.6943          | 0.7897   |
| 0.7311        | 2.7   | 1700 | 0.7353          | 0.7714   |
| 0.7181        | 2.86  | 1800 | 0.6831          | 0.7921   |
| 0.5986        | 3.02  | 1900 | 0.6930          | 0.7897   |
| 0.5716        | 3.17  | 2000 | 0.6685          | 0.8048   |
| 0.5218        | 3.33  | 2100 | 0.7152          | 0.7917   |
| 0.8469        | 3.49  | 2200 | 0.6405          | 0.8020   |
| 0.5783        | 3.65  | 2300 | 0.6728          | 0.7956   |
| 0.7202        | 3.81  | 2400 | 0.6007          | 0.8155   |
| 0.5525        | 3.97  | 2500 | 0.6559          | 0.8056   |
| 0.519         | 4.13  | 2600 | 0.5868          | 0.8222   |
| 0.6171        | 4.29  | 2700 | 0.6157          | 0.8103   |
| 0.5401        | 4.44  | 2800 | 0.6120          | 0.8083   |
| 0.6105        | 4.6   | 2900 | 0.5619          | 0.8325   |
| 0.7497        | 4.76  | 3000 | 0.5859          | 0.8302   |
| 0.4856        | 4.92  | 3100 | 0.5833          | 0.8262   |
| 0.4959        | 5.08  | 3200 | 0.5704          | 0.8329   |
| 0.4413        | 5.24  | 3300 | 0.6217          | 0.8190   |
| 0.4513        | 5.4   | 3400 | 0.5750          | 0.8294   |
| 0.3987        | 5.56  | 3500 | 0.5826          | 0.8341   |
| 0.4395        | 5.71  | 3600 | 0.5754          | 0.8385   |
| 0.4669        | 5.87  | 3700 | 0.5653          | 0.8357   |
| 0.4005        | 6.03  | 3800 | 0.5424          | 0.8377   |
| 0.4457        | 6.19  | 3900 | 0.5620          | 0.8393   |
| 0.3693        | 6.35  | 4000 | 0.5411          | 0.8413   |
| 0.2933        | 6.51  | 4100 | 0.5325          | 0.8484   |
| 0.2603        | 6.67  | 4200 | 0.5360          | 0.8476   |
| 0.3364        | 6.83  | 4300 | 0.5303          | 0.8496   |
| 0.3639        | 6.98  | 4400 | 0.5316          | 0.8492   |


### Framework versions

- Transformers 4.39.3
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2