---
license: apache-2.0
tags:
- image-classification
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: vit-accident-image
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# vit-accident-image

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 accident classification dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2027
- Accuracy: 0.93
- F1: 0.9301

## Model description

label 0 : non-accident , label 1 : accident-detected

## 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: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 0.3546        | 2.0   | 100  | 0.2327          | 0.9184   | 0.9184 |
| 0.1654        | 4.0   | 200  | 0.2075          | 0.9388   | 0.9388 |
| 0.0146        | 6.0   | 300  | 0.2497          | 0.9388   | 0.9387 |
| 0.0317        | 8.0   | 400  | 0.2179          | 0.9286   | 0.9285 |
| 0.0192        | 10.0  | 500  | 0.2255          | 0.9286   | 0.9286 |


### Framework versions

- Transformers 4.30.0
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.13.3