---
license: apache-2.0
tags:
- image-classification
- vision
- generated_from_trainer
metrics:
- f1
model-index:
- name: vit-base-patch32-224-in21-leicester_binary
  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. -->

# vit-base-patch32-224-in21-leicester_binary

This model is a fine-tuned version of [google/vit-base-patch32-224-in21k](https://huggingface.co/google/vit-base-patch32-224-in21k) on the davanstrien/leicester_loaded_annotations_binary dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0949
- F1: 0.9747

## 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: 2e-05
- train_batch_size: 64
- eval_batch_size: 128
- seed: 1337
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 40.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| No log        | 1.0   | 7    | 0.4576          | 0.8608 |
| 0.5021        | 2.0   | 14   | 0.3953          | 0.8608 |
| 0.3595        | 3.0   | 21   | 0.3809          | 0.8608 |
| 0.3595        | 4.0   | 28   | 0.3286          | 0.8608 |
| 0.3009        | 5.0   | 35   | 0.2945          | 0.8608 |
| 0.2843        | 6.0   | 42   | 0.3528          | 0.8608 |
| 0.2843        | 7.0   | 49   | 0.2345          | 0.8608 |
| 0.266         | 8.0   | 56   | 0.2499          | 0.8608 |
| 0.222         | 9.0   | 63   | 0.2544          | 0.8608 |
| 0.2018        | 10.0  | 70   | 0.1954          | 0.8608 |
| 0.2018        | 11.0  | 77   | 0.2351          | 0.8608 |
| 0.1948        | 12.0  | 84   | 0.1705          | 0.8608 |
| 0.2053        | 13.0  | 91   | 0.1625          | 0.8734 |
| 0.2053        | 14.0  | 98   | 0.1719          | 0.9367 |
| 0.1729        | 15.0  | 105  | 0.1489          | 0.9367 |
| 0.1535        | 16.0  | 112  | 0.1450          | 0.9494 |
| 0.1535        | 17.0  | 119  | 0.1750          | 0.9494 |
| 0.1492        | 18.0  | 126  | 0.1514          | 0.9494 |
| 0.1349        | 19.0  | 133  | 0.1304          | 0.9620 |
| 0.1538        | 20.0  | 140  | 0.1291          | 0.9620 |
| 0.1538        | 21.0  | 147  | 0.1306          | 0.9620 |
| 0.1357        | 22.0  | 154  | 0.1283          | 0.9620 |
| 0.147         | 23.0  | 161  | 0.1289          | 0.9494 |
| 0.147         | 24.0  | 168  | 0.1339          | 0.9747 |
| 0.1388        | 25.0  | 175  | 0.1244          | 0.9494 |
| 0.1192        | 26.0  | 182  | 0.1117          | 0.9747 |
| 0.1192        | 27.0  | 189  | 0.1105          | 0.9873 |
| 0.112         | 28.0  | 196  | 0.1079          | 0.9747 |
| 0.1215        | 29.0  | 203  | 0.1151          | 0.9620 |
| 0.1139        | 30.0  | 210  | 0.1008          | 0.9873 |
| 0.1139        | 31.0  | 217  | 0.1033          | 0.9747 |
| 0.1164        | 32.0  | 224  | 0.0985          | 0.9873 |
| 0.1192        | 33.0  | 231  | 0.0955          | 0.9873 |
| 0.1192        | 34.0  | 238  | 0.1077          | 0.9620 |
| 0.1132        | 35.0  | 245  | 0.1107          | 0.9620 |
| 0.1021        | 36.0  | 252  | 0.0958          | 0.9873 |
| 0.1021        | 37.0  | 259  | 0.0957          | 0.9873 |
| 0.0945        | 38.0  | 266  | 0.0951          | 0.9747 |
| 0.1244        | 39.0  | 273  | 0.0949          | 0.9747 |
| 0.1012        | 40.0  | 280  | 0.0955          | 0.9873 |


### Framework versions

- Transformers 4.26.0.dev0
- Pytorch 1.12.1+cu113
- Datasets 2.7.1
- Tokenizers 0.13.2