---
library_name: transformers
license: apache-2.0
base_model: google/vit-base-patch16-224
tags:
- image-classification
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: dvm-cars-vit-first-5k
  results:
  - task:
      name: Image Classification
      type: image-classification
    dataset:
      name: TalonMeyer/dvm-cars-dataset-first-5k
      type: imagefolder
      config: default
      split: validation
      args: default
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.4431137724550898
---

<!-- 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. -->

# dvm-cars-vit-first-5k

This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on the TalonMeyer/dvm-cars-dataset-first-5k dataset.
It achieves the following results on the evaluation set:
- Loss: 2.3711
- Accuracy: 0.4431

## 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: 0.0003
- 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: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 3.1701        | 1.0   | 251  | 2.9441          | 0.2994   |
| 2.5577        | 2.0   | 502  | 2.6693          | 0.3333   |
| 2.3469        | 3.0   | 753  | 2.5099          | 0.3593   |
| 2.1792        | 4.0   | 1004 | 2.4285          | 0.4032   |
| 2.0967        | 5.0   | 1255 | 2.4063          | 0.4152   |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1