---
license: apache-2.0
base_model: microsoft/beit-large-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: smids_10x_beit_large_adamax_00001_fold1
  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: 0.9282136894824707
---

<!-- 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. -->

# smids_10x_beit_large_adamax_00001_fold1

This model is a fine-tuned version of [microsoft/beit-large-patch16-224](https://huggingface.co/microsoft/beit-large-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8887
- Accuracy: 0.9282

## 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: 1e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.1288        | 1.0   | 751   | 0.2785          | 0.9065   |
| 0.0676        | 2.0   | 1502  | 0.3146          | 0.9149   |
| 0.0264        | 3.0   | 2253  | 0.4181          | 0.9115   |
| 0.025         | 4.0   | 3004  | 0.5488          | 0.9199   |
| 0.0069        | 5.0   | 3755  | 0.5526          | 0.9182   |
| 0.0049        | 6.0   | 4506  | 0.6296          | 0.9165   |
| 0.0005        | 7.0   | 5257  | 0.7054          | 0.9149   |
| 0.0001        | 8.0   | 6008  | 0.7404          | 0.9182   |
| 0.0362        | 9.0   | 6759  | 0.7520          | 0.9132   |
| 0.0001        | 10.0  | 7510  | 0.8011          | 0.9149   |
| 0.0001        | 11.0  | 8261  | 0.7591          | 0.9199   |
| 0.0002        | 12.0  | 9012  | 0.7216          | 0.9215   |
| 0.0024        | 13.0  | 9763  | 0.8101          | 0.9132   |
| 0.0           | 14.0  | 10514 | 0.8382          | 0.9249   |
| 0.0           | 15.0  | 11265 | 0.8571          | 0.9165   |
| 0.0           | 16.0  | 12016 | 0.8307          | 0.9249   |
| 0.0002        | 17.0  | 12767 | 0.8135          | 0.9098   |
| 0.0           | 18.0  | 13518 | 0.9070          | 0.9132   |
| 0.0           | 19.0  | 14269 | 0.8650          | 0.9115   |
| 0.0           | 20.0  | 15020 | 0.8297          | 0.9265   |
| 0.0           | 21.0  | 15771 | 0.8359          | 0.9282   |
| 0.0           | 22.0  | 16522 | 0.8827          | 0.9265   |
| 0.0           | 23.0  | 17273 | 0.8484          | 0.9215   |
| 0.0           | 24.0  | 18024 | 0.8739          | 0.9182   |
| 0.0004        | 25.0  | 18775 | 0.8728          | 0.9232   |
| 0.0           | 26.0  | 19526 | 0.8742          | 0.9149   |
| 0.0           | 27.0  | 20277 | 0.9029          | 0.9199   |
| 0.0           | 28.0  | 21028 | 0.8812          | 0.9232   |
| 0.0109        | 29.0  | 21779 | 0.9326          | 0.9215   |
| 0.0           | 30.0  | 22530 | 0.9197          | 0.9115   |
| 0.0001        | 31.0  | 23281 | 0.8910          | 0.9215   |
| 0.0           | 32.0  | 24032 | 0.8659          | 0.9215   |
| 0.0           | 33.0  | 24783 | 0.8759          | 0.9232   |
| 0.0           | 34.0  | 25534 | 0.9176          | 0.9199   |
| 0.0           | 35.0  | 26285 | 0.8674          | 0.9249   |
| 0.0           | 36.0  | 27036 | 0.8364          | 0.9249   |
| 0.0           | 37.0  | 27787 | 0.8518          | 0.9265   |
| 0.0           | 38.0  | 28538 | 0.8614          | 0.9232   |
| 0.0           | 39.0  | 29289 | 0.8789          | 0.9215   |
| 0.0           | 40.0  | 30040 | 0.8979          | 0.9215   |
| 0.0           | 41.0  | 30791 | 0.9262          | 0.9199   |
| 0.0107        | 42.0  | 31542 | 0.8969          | 0.9232   |
| 0.0           | 43.0  | 32293 | 0.9021          | 0.9265   |
| 0.0           | 44.0  | 33044 | 0.8921          | 0.9282   |
| 0.0           | 45.0  | 33795 | 0.9002          | 0.9249   |
| 0.0007        | 46.0  | 34546 | 0.9147          | 0.9199   |
| 0.0           | 47.0  | 35297 | 0.8904          | 0.9249   |
| 0.0           | 48.0  | 36048 | 0.8842          | 0.9282   |
| 0.0           | 49.0  | 36799 | 0.8899          | 0.9265   |
| 0.0           | 50.0  | 37550 | 0.8887          | 0.9282   |


### Framework versions

- Transformers 4.32.1
- Pytorch 2.1.0+cu121
- Datasets 2.12.0
- Tokenizers 0.13.2