---
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_0001_fold3
  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: 0.9069767441860465
---

<!-- 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_0001_fold3

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: 1.4238
- Accuracy: 0.9070

## 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: 0.0001
- 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.0397        | 1.0   | 217   | 0.4585          | 0.8605   |
| 0.0001        | 2.0   | 434   | 1.0180          | 0.8837   |
| 0.0           | 3.0   | 651   | 0.9542          | 0.9070   |
| 0.0           | 4.0   | 868   | 1.0472          | 0.9070   |
| 0.011         | 5.0   | 1085  | 0.8152          | 0.8837   |
| 0.0           | 6.0   | 1302  | 0.8047          | 0.9070   |
| 0.0001        | 7.0   | 1519  | 1.1339          | 0.8837   |
| 0.0           | 8.0   | 1736  | 0.6894          | 0.9070   |
| 0.0           | 9.0   | 1953  | 0.9352          | 0.8837   |
| 0.0015        | 10.0  | 2170  | 0.8497          | 0.8372   |
| 0.0           | 11.0  | 2387  | 0.8859          | 0.8837   |
| 0.0           | 12.0  | 2604  | 1.0189          | 0.8837   |
| 0.001         | 13.0  | 2821  | 0.9729          | 0.8605   |
| 0.0           | 14.0  | 3038  | 0.9152          | 0.8837   |
| 0.0           | 15.0  | 3255  | 0.8697          | 0.8605   |
| 0.0           | 16.0  | 3472  | 0.9016          | 0.8605   |
| 0.0           | 17.0  | 3689  | 0.8964          | 0.8837   |
| 0.0           | 18.0  | 3906  | 1.0277          | 0.8837   |
| 0.0           | 19.0  | 4123  | 0.8584          | 0.8837   |
| 0.0           | 20.0  | 4340  | 0.8132          | 0.9070   |
| 0.0           | 21.0  | 4557  | 0.8453          | 0.9070   |
| 0.0           | 22.0  | 4774  | 0.8777          | 0.9070   |
| 0.0           | 23.0  | 4991  | 0.8912          | 0.9070   |
| 0.0           | 24.0  | 5208  | 0.9167          | 0.8837   |
| 0.0           | 25.0  | 5425  | 0.9234          | 0.8837   |
| 0.0           | 26.0  | 5642  | 0.9407          | 0.8837   |
| 0.0           | 27.0  | 5859  | 1.0058          | 0.9070   |
| 0.0           | 28.0  | 6076  | 1.1055          | 0.8837   |
| 0.0           | 29.0  | 6293  | 1.1155          | 0.8837   |
| 0.0           | 30.0  | 6510  | 1.1212          | 0.8837   |
| 0.0           | 31.0  | 6727  | 1.4063          | 0.9070   |
| 0.0           | 32.0  | 6944  | 1.3993          | 0.9070   |
| 0.0           | 33.0  | 7161  | 1.4033          | 0.9070   |
| 0.0           | 34.0  | 7378  | 1.4032          | 0.9070   |
| 0.0           | 35.0  | 7595  | 1.4070          | 0.9070   |
| 0.0           | 36.0  | 7812  | 1.4100          | 0.9070   |
| 0.0           | 37.0  | 8029  | 1.4111          | 0.9070   |
| 0.0           | 38.0  | 8246  | 1.4234          | 0.9070   |
| 0.0           | 39.0  | 8463  | 1.4283          | 0.8837   |
| 0.0           | 40.0  | 8680  | 1.4259          | 0.8837   |
| 0.0           | 41.0  | 8897  | 1.4283          | 0.8837   |
| 0.0           | 42.0  | 9114  | 1.4459          | 0.8837   |
| 0.0           | 43.0  | 9331  | 1.4466          | 0.8837   |
| 0.0           | 44.0  | 9548  | 1.4349          | 0.8837   |
| 0.0           | 45.0  | 9765  | 1.4277          | 0.8837   |
| 0.0           | 46.0  | 9982  | 1.4129          | 0.9070   |
| 0.0           | 47.0  | 10199 | 1.4175          | 0.9070   |
| 0.0           | 48.0  | 10416 | 1.4184          | 0.9070   |
| 0.0           | 49.0  | 10633 | 1.4243          | 0.9070   |
| 0.0           | 50.0  | 10850 | 1.4238          | 0.9070   |


### Framework versions

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