---
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_3Class_RMSprop_1-e5_20Epoch_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: 0.8310279359913209
---

<!-- 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_3Class_RMSprop_1-e5_20Epoch_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: 1.7877
- Accuracy: 0.8310

## 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: 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.5804        | 1.0   | 924   | 0.4986          | 0.8004   |
| 0.4299        | 2.0   | 1848  | 0.4370          | 0.8248   |
| 0.2235        | 3.0   | 2772  | 0.4410          | 0.8446   |
| 0.1347        | 4.0   | 3696  | 0.5720          | 0.8343   |
| 0.0488        | 5.0   | 4620  | 0.8207          | 0.8275   |
| 0.2009        | 6.0   | 5544  | 1.0317          | 0.8329   |
| 0.0566        | 7.0   | 6468  | 1.3823          | 0.8205   |
| 0.0733        | 8.0   | 7392  | 1.3466          | 0.8324   |
| 0.0357        | 9.0   | 8316  | 1.3267          | 0.8362   |
| 0.071         | 10.0  | 9240  | 1.5459          | 0.8264   |
| 0.0505        | 11.0  | 10164 | 1.6231          | 0.8280   |
| 0.1165        | 12.0  | 11088 | 1.6016          | 0.8297   |
| 0.0243        | 13.0  | 12012 | 1.7023          | 0.8351   |
| 0.0327        | 14.0  | 12936 | 1.6673          | 0.8354   |
| 0.002         | 15.0  | 13860 | 1.7768          | 0.8259   |
| 0.0008        | 16.0  | 14784 | 1.8057          | 0.8302   |
| 0.0117        | 17.0  | 15708 | 1.8092          | 0.8253   |
| 0.024         | 18.0  | 16632 | 1.7701          | 0.8324   |
| 0.0349        | 19.0  | 17556 | 1.7881          | 0.8291   |
| 0.0001        | 20.0  | 18480 | 1.7877          | 0.8310   |


### Framework versions

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