---
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
- image-classification
- generated_from_trainer
metrics:
- f1
model-index:
- name: all-observation-type
  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. -->

# all-observation-type

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 all-multi-class dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0077
- F1: 0.0913

## 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: 0.0002
- 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: 40
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | F1     |
|:-------------:|:-------:|:----:|:---------------:|:------:|
| 0.0726        | 1.1628  | 100  | 0.0660          | 0.0    |
| 0.0264        | 2.3256  | 200  | 0.0247          | 0.0    |
| 0.0161        | 3.4884  | 300  | 0.0165          | 0.0    |
| 0.0133        | 4.6512  | 400  | 0.0135          | 0.0    |
| 0.0124        | 5.8140  | 500  | 0.0120          | 0.0    |
| 0.011         | 6.9767  | 600  | 0.0112          | 0.0    |
| 0.0114        | 8.1395  | 700  | 0.0107          | 0.0    |
| 0.0109        | 9.3023  | 800  | 0.0103          | 0.0    |
| 0.0096        | 10.4651 | 900  | 0.0102          | 0.0    |
| 0.0099        | 11.6279 | 1000 | 0.0098          | 0.0    |
| 0.0089        | 12.7907 | 1100 | 0.0094          | 0.0    |
| 0.0091        | 13.9535 | 1200 | 0.0093          | 0.0    |
| 0.0081        | 15.1163 | 1300 | 0.0089          | 0.0    |
| 0.0073        | 16.2791 | 1400 | 0.0089          | 0.0    |
| 0.0071        | 17.4419 | 1500 | 0.0085          | 0.0    |
| 0.0068        | 18.6047 | 1600 | 0.0082          | 0.0183 |
| 0.0064        | 19.7674 | 1700 | 0.0082          | 0.0365 |
| 0.0061        | 20.9302 | 1800 | 0.0086          | 0.0091 |
| 0.0054        | 22.0930 | 1900 | 0.0082          | 0.0594 |
| 0.0051        | 23.2558 | 2000 | 0.0080          | 0.0502 |
| 0.0048        | 24.4186 | 2100 | 0.0079          | 0.0639 |
| 0.0045        | 25.5814 | 2200 | 0.0080          | 0.0639 |
| 0.0036        | 26.7442 | 2300 | 0.0079          | 0.1027 |
| 0.0038        | 27.9070 | 2400 | 0.0079          | 0.1027 |
| 0.0032        | 29.0698 | 2500 | 0.0077          | 0.0913 |
| 0.004         | 30.2326 | 2600 | 0.0079          | 0.1027 |
| 0.003         | 31.3953 | 2700 | 0.0081          | 0.0936 |
| 0.0029        | 32.5581 | 2800 | 0.0080          | 0.0890 |
| 0.0033        | 33.7209 | 2900 | 0.0081          | 0.0845 |
| 0.0029        | 34.8837 | 3000 | 0.0081          | 0.1256 |
| 0.0025        | 36.0465 | 3100 | 0.0081          | 0.1347 |
| 0.0027        | 37.2093 | 3200 | 0.0081          | 0.1324 |
| 0.0028        | 38.3721 | 3300 | 0.0082          | 0.1324 |
| 0.0023        | 39.5349 | 3400 | 0.0082          | 0.1324 |


### Framework versions

- Transformers 4.40.2
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1