---
library_name: transformers
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
- image-classification
- vision
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: vit-base-beans
  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-beans

This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the beans dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0079
- Accuracy: 1.0

## 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: 8
- eval_batch_size: 8
- seed: 1337
- distributed_type: multi-GPU
- num_devices: 2
- total_train_batch_size: 16
- total_eval_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5.0

### Training results

| Training Loss | Epoch | Step | Accuracy | Validation Loss |
|:-------------:|:-----:|:----:|:--------:|:---------------:|
| 0.2859        | 1.0   | 130  | 0.9624   | 0.2189          |
| 0.1316        | 2.0   | 260  | 0.9699   | 0.1334          |
| 0.1438        | 3.0   | 390  | 0.9699   | 0.0981          |
| 0.0833        | 4.0   | 520  | 0.9925   | 0.0656          |
| 0.1107        | 5.0   | 650  | 0.9774   | 0.0817          |
| 0.098         | 11.0  | 715  | 0.9925   | 0.0570          |
| 0.0935        | 12.0  | 780  | 1.0      | 0.0418          |
| 0.0907        | 13.0  | 845  | 0.9699   | 0.1093          |
| 0.0947        | 14.0  | 910  | 1.0      | 0.0347          |
| 0.1259        | 15.0  | 975  | 0.9850   | 0.0710          |
| 0.0325        | 16.0  | 1040 | 0.9774   | 0.0587          |
| 0.1397        | 17.0  | 1105 | 0.9925   | 0.0495          |
| 0.0456        | 18.0  | 1170 | 0.9774   | 0.0519          |
| 0.0439        | 19.0  | 1235 | 1.0      | 0.0216          |
| 0.0484        | 20.0  | 1300 | 0.9925   | 0.0316          |
| 0.0276        | 21.0  | 1365 | 1.0      | 0.0192          |
| 0.0348        | 22.0  | 1430 | 1.0      | 0.0177          |
| 0.0326        | 23.0  | 1495 | 1.0      | 0.0175          |
| 0.1014        | 24.0  | 1560 | 0.9925   | 0.0235          |
| 0.0395        | 25.0  | 1625 | 0.9850   | 0.0451          |
| 0.0265        | 26.0  | 1690 | 0.9925   | 0.0297          |
| 0.0569        | 27.0  | 1755 | 0.9925   | 0.0263          |
| 0.0666        | 28.0  | 1820 | 0.9850   | 0.0245          |
| 0.0285        | 29.0  | 1885 | 0.9774   | 0.0418          |
| 0.0892        | 30.0  | 1950 | 0.9925   | 0.0204          |
| 0.0371        | 31.0  | 2015 | 0.9850   | 0.0339          |
| 0.0105        | 32.0  | 2080 | 1.0      | 0.0143          |
| 0.0563        | 33.0  | 2145 | 1.0      | 0.0140          |
| 0.0573        | 34.0  | 2210 | 1.0      | 0.0102          |
| 0.0409        | 35.0  | 2275 | 1.0      | 0.0096          |
| 0.0523        | 36.0  | 2340 | 0.9925   | 0.0149          |
| 0.0131        | 37.0  | 2405 | 0.9925   | 0.0197          |
| 0.0329        | 38.0  | 2470 | 1.0      | 0.0109          |
| 0.0577        | 39.0  | 2535 | 1.0      | 0.0096          |
| 0.0085        | 40.0  | 2600 | 0.9925   | 0.0147          |
| 0.0618        | 41.0  | 2665 | 1.0      | 0.0094          |
| 0.0847        | 42.0  | 2730 | 0.9925   | 0.0197          |
| 0.0291        | 43.0  | 2795 | 1.0      | 0.0089          |
| 0.0568        | 44.0  | 2860 | 1.0      | 0.0087          |
| 0.0077        | 45.0  | 2925 | 1.0      | 0.0104          |
| 0.008         | 46.0  | 2990 | 1.0      | 0.0138          |
| 0.0272        | 47.0  | 3055 | 1.0      | 0.0081          |
| 0.008         | 48.0  | 3120 | 1.0      | 0.0084          |
| 0.0112        | 49.0  | 3185 | 1.0      | 0.0082          |
| 0.013         | 50.0  | 3250 | 1.0      | 0.0079          |


### Framework versions

- Transformers 4.45.0.dev0
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1