---
license: apache-2.0
base_model: microsoft/beit-base-patch16-224-pt22k-ft22k
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: Boya1_RMSProp_1-e5_20Epoch_09Momentum_Beit-base-patch16_fold5
  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: 0.649850827230811
---

<!-- 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. -->

# Boya1_RMSProp_1-e5_20Epoch_09Momentum_Beit-base-patch16_fold5

This model is a fine-tuned version of [microsoft/beit-base-patch16-224-pt22k-ft22k](https://huggingface.co/microsoft/beit-base-patch16-224-pt22k-ft22k) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 3.1823
- Accuracy: 0.6499

## 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: 16
- eval_batch_size: 16
- 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: 20

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 1.1635        | 1.0   | 924   | 1.1860          | 0.5948   |
| 1.0619        | 2.0   | 1848  | 1.0310          | 0.6455   |
| 0.646         | 3.0   | 2772  | 1.0620          | 0.6509   |
| 0.3294        | 4.0   | 3696  | 1.2169          | 0.6599   |
| 0.2648        | 5.0   | 4620  | 1.4374          | 0.6455   |
| 0.1957        | 6.0   | 5544  | 1.7164          | 0.6420   |
| 0.131         | 7.0   | 6468  | 2.0272          | 0.6488   |
| 0.0817        | 8.0   | 7392  | 2.2750          | 0.6447   |
| 0.0483        | 9.0   | 8316  | 2.4384          | 0.6431   |
| 0.0451        | 10.0  | 9240  | 2.6186          | 0.6447   |
| 0.0224        | 11.0  | 10164 | 2.7368          | 0.6463   |
| 0.0134        | 12.0  | 11088 | 2.9439          | 0.6477   |
| 0.0023        | 13.0  | 12012 | 2.9691          | 0.6520   |
| 0.0074        | 14.0  | 12936 | 3.0721          | 0.6450   |
| 0.0231        | 15.0  | 13860 | 3.1373          | 0.6499   |
| 0.0004        | 16.0  | 14784 | 3.2089          | 0.6474   |
| 0.0062        | 17.0  | 15708 | 3.1483          | 0.6493   |
| 0.0132        | 18.0  | 16632 | 3.1830          | 0.6515   |
| 0.0034        | 19.0  | 17556 | 3.1843          | 0.6474   |
| 0.0796        | 20.0  | 18480 | 3.1823          | 0.6499   |


### Framework versions

- Transformers 4.35.0
- Pytorch 2.1.0
- Datasets 2.14.6
- Tokenizers 0.14.1