---
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_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: 0.8259571001900624
---

<!-- 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_fold1

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: 1.7955
- Accuracy: 0.8260

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.4439        | 1.0   | 924   | 0.4590          | 0.8091   |
| 0.3875        | 2.0   | 1848  | 0.4469          | 0.8227   |
| 0.2939        | 3.0   | 2772  | 0.5412          | 0.8154   |
| 0.1247        | 4.0   | 3696  | 0.6692          | 0.8213   |
| 0.1513        | 5.0   | 4620  | 0.8256          | 0.8227   |
| 0.1409        | 6.0   | 5544  | 1.1386          | 0.8181   |
| 0.0278        | 7.0   | 6468  | 1.3459          | 0.8189   |
| 0.013         | 8.0   | 7392  | 1.5383          | 0.8175   |
| 0.0037        | 9.0   | 8316  | 1.5542          | 0.8254   |
| 0.0119        | 10.0  | 9240  | 1.6982          | 0.8178   |
| 0.0008        | 11.0  | 10164 | 1.7834          | 0.8178   |
| 0.0799        | 12.0  | 11088 | 1.6908          | 0.8230   |
| 0.0845        | 13.0  | 12012 | 1.7310          | 0.8200   |
| 0.0588        | 14.0  | 12936 | 1.7389          | 0.8235   |
| 0.0004        | 15.0  | 13860 | 1.8086          | 0.8246   |
| 0.0004        | 16.0  | 14784 | 1.8040          | 0.8262   |
| 0.0009        | 17.0  | 15708 | 1.7272          | 0.8243   |
| 0.0021        | 18.0  | 16632 | 1.7738          | 0.8238   |
| 0.0559        | 19.0  | 17556 | 1.8013          | 0.8254   |
| 0.0           | 20.0  | 18480 | 1.7955          | 0.8260   |


### Framework versions

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