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---
license: apache-2.0
base_model: google/vit-base-patch16-224
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: vit-base-patch16-224-finetuned-traffic
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. -->
# Traffic level image classification
This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4394
- Accuracy: 0.8292
- Precision: 0.8232
- Recall: 0.7366
- F1: 0.7721
## Model description
Built from 6,000 images fetched from public traffic cameras in Norway to classify traffic levels from low, medium to high. Dataset is unbalanced skewed towards low traffic images.
## 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: 5e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 5
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|:-------------:|:------:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.6282 | 0.9843 | 47 | 0.5725 | 0.7644 | 0.7933 | 0.5918 | 0.6525 |
| 0.4486 | 1.9895 | 95 | 0.4630 | 0.8012 | 0.7964 | 0.6824 | 0.7213 |
| 0.3285 | 2.9948 | 143 | 0.4394 | 0.8292 | 0.8232 | 0.7366 | 0.7721 |
| 0.2391 | 4.0 | 191 | 0.4302 | 0.8115 | 0.7941 | 0.7333 | 0.7555 |
| 0.1814 | 4.9215 | 235 | 0.4365 | 0.8218 | 0.7993 | 0.7362 | 0.7631 |
### Framework versions
- Transformers 4.40.1
- Pytorch 2.2.1+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1
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