metadata
license: apache-2.0
tags:
- image-classification
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: vit-accident-image
results: []
vit-accident-image
This model is a fine-tuned version of 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