---
license: apache-2.0
base_model: google/vit-base-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: vit-base-patch16-224-finetuned-context-classifier
  results:
  - task:
      name: Image Classification
      type: image-classification
    dataset:
      name: imagefolder
      type: imagefolder
      config: default
      split: test
      args: default
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.8187702265372169
---

<!-- 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. -->

# vit-base-patch16-224-finetuned-context-classifier

This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7157
- Accuracy: 0.8188

## 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: 5e-05
- train_batch_size: 128
- eval_batch_size: 128
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 512
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 100

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.3586        | 2.0   | 10   | 1.2322          | 0.3916   |
| 1.0841        | 4.0   | 20   | 0.8444          | 0.6958   |
| 0.7282        | 6.0   | 30   | 0.5498          | 0.7767   |
| 0.4768        | 8.0   | 40   | 0.4273          | 0.8155   |
| 0.3332        | 10.0  | 50   | 0.4059          | 0.8220   |
| 0.242         | 12.0  | 60   | 0.4272          | 0.8252   |
| 0.1737        | 14.0  | 70   | 0.4372          | 0.8188   |
| 0.1266        | 16.0  | 80   | 0.4495          | 0.8123   |
| 0.1089        | 18.0  | 90   | 0.4877          | 0.8091   |
| 0.0837        | 20.0  | 100  | 0.5318          | 0.8058   |
| 0.0687        | 22.0  | 110  | 0.5300          | 0.7961   |
| 0.0667        | 24.0  | 120  | 0.6253          | 0.7994   |
| 0.0581        | 26.0  | 130  | 0.5495          | 0.8220   |
| 0.0574        | 28.0  | 140  | 0.5646          | 0.8188   |
| 0.0564        | 30.0  | 150  | 0.5990          | 0.8252   |
| 0.0492        | 32.0  | 160  | 0.6436          | 0.8155   |
| 0.0406        | 34.0  | 170  | 0.6225          | 0.8091   |
| 0.0411        | 36.0  | 180  | 0.6168          | 0.8123   |
| 0.0381        | 38.0  | 190  | 0.6731          | 0.8123   |
| 0.0358        | 40.0  | 200  | 0.6198          | 0.7961   |
| 0.0354        | 42.0  | 210  | 0.6216          | 0.8091   |
| 0.0358        | 44.0  | 220  | 0.6933          | 0.8091   |
| 0.037         | 46.0  | 230  | 0.6488          | 0.8188   |
| 0.0344        | 48.0  | 240  | 0.6546          | 0.8220   |
| 0.0335        | 50.0  | 250  | 0.6399          | 0.7994   |
| 0.0297        | 52.0  | 260  | 0.6553          | 0.8123   |
| 0.0318        | 54.0  | 270  | 0.6996          | 0.7896   |
| 0.0254        | 56.0  | 280  | 0.6809          | 0.7961   |
| 0.0322        | 58.0  | 290  | 0.7048          | 0.7896   |
| 0.024         | 60.0  | 300  | 0.6869          | 0.8123   |
| 0.0255        | 62.0  | 310  | 0.7099          | 0.8058   |
| 0.0266        | 64.0  | 320  | 0.6894          | 0.8091   |
| 0.0243        | 66.0  | 330  | 0.7604          | 0.8091   |
| 0.0232        | 68.0  | 340  | 0.6983          | 0.8123   |
| 0.019         | 70.0  | 350  | 0.6834          | 0.8091   |
| 0.0235        | 72.0  | 360  | 0.7102          | 0.8091   |
| 0.0262        | 74.0  | 370  | 0.6902          | 0.8155   |
| 0.0206        | 76.0  | 380  | 0.6662          | 0.8091   |
| 0.0238        | 78.0  | 390  | 0.7109          | 0.8220   |
| 0.0202        | 80.0  | 400  | 0.7061          | 0.8058   |
| 0.0204        | 82.0  | 410  | 0.7291          | 0.8155   |
| 0.0231        | 84.0  | 420  | 0.7103          | 0.8091   |
| 0.0217        | 86.0  | 430  | 0.7050          | 0.8123   |
| 0.021         | 88.0  | 440  | 0.7037          | 0.8155   |
| 0.0207        | 90.0  | 450  | 0.6996          | 0.8058   |
| 0.0163        | 92.0  | 460  | 0.7137          | 0.8091   |
| 0.0181        | 94.0  | 470  | 0.7153          | 0.8155   |
| 0.0225        | 96.0  | 480  | 0.7105          | 0.8123   |
| 0.0185        | 98.0  | 490  | 0.7140          | 0.8155   |
| 0.0219        | 100.0 | 500  | 0.7157          | 0.8188   |


### Framework versions

- Transformers 4.35.0
- Pytorch 2.1.0+cu121
- Datasets 2.14.4
- Tokenizers 0.14.1