---
license: apache-2.0
base_model: microsoft/beit-large-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: hushem_40x_beit_large_adamax_00001_fold4
  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: 1.0
---

<!-- 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. -->

# hushem_40x_beit_large_adamax_00001_fold4

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: 0.0038
- 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: 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.0209        | 1.0   | 219   | 0.0613          | 0.9762   |
| 0.0077        | 2.0   | 438   | 0.0174          | 1.0      |
| 0.0003        | 3.0   | 657   | 0.0464          | 0.9762   |
| 0.0004        | 4.0   | 876   | 0.0760          | 0.9762   |
| 0.0062        | 5.0   | 1095  | 0.0813          | 0.9762   |
| 0.0001        | 6.0   | 1314  | 0.0164          | 1.0      |
| 0.0002        | 7.0   | 1533  | 0.0181          | 1.0      |
| 0.0002        | 8.0   | 1752  | 0.0299          | 0.9762   |
| 0.0           | 9.0   | 1971  | 0.0028          | 1.0      |
| 0.0001        | 10.0  | 2190  | 0.0137          | 1.0      |
| 0.0001        | 11.0  | 2409  | 0.0028          | 1.0      |
| 0.0           | 12.0  | 2628  | 0.0068          | 1.0      |
| 0.0           | 13.0  | 2847  | 0.0011          | 1.0      |
| 0.0           | 14.0  | 3066  | 0.0415          | 0.9762   |
| 0.0           | 15.0  | 3285  | 0.0029          | 1.0      |
| 0.0003        | 16.0  | 3504  | 0.0012          | 1.0      |
| 0.0           | 17.0  | 3723  | 0.0002          | 1.0      |
| 0.0           | 18.0  | 3942  | 0.0203          | 0.9762   |
| 0.0           | 19.0  | 4161  | 0.0016          | 1.0      |
| 0.0           | 20.0  | 4380  | 0.0412          | 0.9762   |
| 0.0           | 21.0  | 4599  | 0.0007          | 1.0      |
| 0.0           | 22.0  | 4818  | 0.0079          | 1.0      |
| 0.0           | 23.0  | 5037  | 0.0005          | 1.0      |
| 0.0001        | 24.0  | 5256  | 0.0050          | 1.0      |
| 0.0           | 25.0  | 5475  | 0.0077          | 1.0      |
| 0.0           | 26.0  | 5694  | 0.0021          | 1.0      |
| 0.0           | 27.0  | 5913  | 0.0004          | 1.0      |
| 0.0           | 28.0  | 6132  | 0.0003          | 1.0      |
| 0.0           | 29.0  | 6351  | 0.0021          | 1.0      |
| 0.0           | 30.0  | 6570  | 0.0005          | 1.0      |
| 0.0           | 31.0  | 6789  | 0.0002          | 1.0      |
| 0.0           | 32.0  | 7008  | 0.0010          | 1.0      |
| 0.0           | 33.0  | 7227  | 0.0045          | 1.0      |
| 0.0           | 34.0  | 7446  | 0.0082          | 1.0      |
| 0.0           | 35.0  | 7665  | 0.0066          | 1.0      |
| 0.0           | 36.0  | 7884  | 0.0009          | 1.0      |
| 0.0           | 37.0  | 8103  | 0.0004          | 1.0      |
| 0.0           | 38.0  | 8322  | 0.0004          | 1.0      |
| 0.0           | 39.0  | 8541  | 0.0101          | 1.0      |
| 0.0           | 40.0  | 8760  | 0.0083          | 1.0      |
| 0.0           | 41.0  | 8979  | 0.0080          | 1.0      |
| 0.0001        | 42.0  | 9198  | 0.0073          | 1.0      |
| 0.0           | 43.0  | 9417  | 0.0042          | 1.0      |
| 0.0           | 44.0  | 9636  | 0.0040          | 1.0      |
| 0.0           | 45.0  | 9855  | 0.0049          | 1.0      |
| 0.0           | 46.0  | 10074 | 0.0031          | 1.0      |
| 0.0           | 47.0  | 10293 | 0.0031          | 1.0      |
| 0.0           | 48.0  | 10512 | 0.0039          | 1.0      |
| 0.0           | 49.0  | 10731 | 0.0040          | 1.0      |
| 0.0           | 50.0  | 10950 | 0.0038          | 1.0      |


### Framework versions

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