---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: V3_Image_classification__points_durs__google_vit-base-patch16-224-in21k
  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. -->

# V3_Image_classification__points_durs__google_vit-base-patch16-224-in21k

This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0411
- Accuracy: 0.9927

## 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: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 50

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.6667        | 1.0   | 15   | 0.5893          | 0.9121   |
| 0.4394        | 2.0   | 30   | 0.3294          | 0.9487   |
| 0.2685        | 3.0   | 45   | 0.1365          | 0.9707   |
| 0.0936        | 4.0   | 60   | 0.0752          | 0.9853   |
| 0.0517        | 5.0   | 75   | 0.0553          | 0.9890   |
| 0.0436        | 6.0   | 90   | 0.0556          | 0.9890   |
| 0.018         | 7.0   | 105  | 0.0557          | 0.9890   |
| 0.0189        | 8.0   | 120  | 0.0457          | 0.9890   |
| 0.013         | 9.0   | 135  | 0.0343          | 0.9927   |
| 0.0115        | 10.0  | 150  | 0.0270          | 0.9963   |
| 0.0101        | 11.0  | 165  | 0.0355          | 0.9927   |
| 0.0085        | 12.0  | 180  | 0.0356          | 0.9927   |
| 0.0079        | 13.0  | 195  | 0.0259          | 0.9963   |
| 0.0069        | 14.0  | 210  | 0.0345          | 0.9927   |
| 0.0066        | 15.0  | 225  | 0.0360          | 0.9927   |
| 0.0061        | 16.0  | 240  | 0.0359          | 0.9927   |
| 0.0059        | 17.0  | 255  | 0.0360          | 0.9927   |
| 0.0055        | 18.0  | 270  | 0.0368          | 0.9927   |
| 0.0054        | 19.0  | 285  | 0.0375          | 0.9927   |
| 0.0051        | 20.0  | 300  | 0.0375          | 0.9927   |
| 0.0049        | 21.0  | 315  | 0.0380          | 0.9927   |
| 0.0047        | 22.0  | 330  | 0.0380          | 0.9927   |
| 0.0046        | 23.0  | 345  | 0.0383          | 0.9927   |
| 0.0044        | 24.0  | 360  | 0.0386          | 0.9927   |
| 0.0043        | 25.0  | 375  | 0.0388          | 0.9927   |
| 0.0041        | 26.0  | 390  | 0.0388          | 0.9927   |
| 0.0041        | 27.0  | 405  | 0.0391          | 0.9927   |
| 0.0039        | 28.0  | 420  | 0.0392          | 0.9927   |
| 0.0038        | 29.0  | 435  | 0.0396          | 0.9927   |
| 0.0037        | 30.0  | 450  | 0.0397          | 0.9927   |
| 0.0037        | 31.0  | 465  | 0.0397          | 0.9927   |
| 0.0036        | 32.0  | 480  | 0.0399          | 0.9927   |
| 0.0035        | 33.0  | 495  | 0.0401          | 0.9927   |
| 0.0034        | 34.0  | 510  | 0.0402          | 0.9927   |
| 0.0034        | 35.0  | 525  | 0.0403          | 0.9927   |
| 0.0033        | 36.0  | 540  | 0.0403          | 0.9927   |
| 0.0033        | 37.0  | 555  | 0.0405          | 0.9927   |
| 0.0032        | 38.0  | 570  | 0.0406          | 0.9927   |
| 0.0032        | 39.0  | 585  | 0.0406          | 0.9927   |
| 0.0031        | 40.0  | 600  | 0.0407          | 0.9927   |
| 0.0031        | 41.0  | 615  | 0.0408          | 0.9927   |
| 0.0031        | 42.0  | 630  | 0.0408          | 0.9927   |
| 0.003         | 43.0  | 645  | 0.0409          | 0.9927   |
| 0.003         | 44.0  | 660  | 0.0410          | 0.9927   |
| 0.003         | 45.0  | 675  | 0.0410          | 0.9927   |
| 0.003         | 46.0  | 690  | 0.0410          | 0.9927   |
| 0.003         | 47.0  | 705  | 0.0410          | 0.9927   |
| 0.0029        | 48.0  | 720  | 0.0411          | 0.9927   |
| 0.0029        | 49.0  | 735  | 0.0411          | 0.9927   |
| 0.0029        | 50.0  | 750  | 0.0411          | 0.9927   |


### Framework versions

- Transformers 4.30.0
- Pytorch 2.1.1
- Datasets 2.15.0
- Tokenizers 0.13.3