---
license: apache-2.0
base_model: microsoft/beit-large-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: Boya1_3Class_SGD_1-e3_20Epoch_Beit-large-224_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: 0.7654086342655444
---

<!-- 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_SGD_1-e3_20Epoch_Beit-large-224_fold1

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: 0.5544
- Accuracy: 0.7654

## 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: 0.001
- 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.9015        | 1.0   | 924   | 0.9341          | 0.6112   |
| 0.8409        | 2.0   | 1848  | 0.7990          | 0.6780   |
| 0.787         | 3.0   | 2772  | 0.7073          | 0.7116   |
| 0.638         | 4.0   | 3696  | 0.6605          | 0.7269   |
| 0.7348        | 5.0   | 4620  | 0.6355          | 0.7355   |
| 0.5951        | 6.0   | 5544  | 0.6177          | 0.7396   |
| 0.6333        | 7.0   | 6468  | 0.6036          | 0.7456   |
| 0.5506        | 8.0   | 7392  | 0.5938          | 0.7491   |
| 0.5249        | 9.0   | 8316  | 0.5879          | 0.7526   |
| 0.7137        | 10.0  | 9240  | 0.5788          | 0.7570   |
| 0.5106        | 11.0  | 10164 | 0.5775          | 0.7575   |
| 0.6297        | 12.0  | 11088 | 0.5685          | 0.7608   |
| 0.5637        | 13.0  | 12012 | 0.5647          | 0.7613   |
| 0.5879        | 14.0  | 12936 | 0.5617          | 0.7632   |
| 0.4454        | 15.0  | 13860 | 0.5588          | 0.7649   |
| 0.522         | 16.0  | 14784 | 0.5607          | 0.7630   |
| 0.551         | 17.0  | 15708 | 0.5549          | 0.7660   |
| 0.6177        | 18.0  | 16632 | 0.5560          | 0.7641   |
| 0.5656        | 19.0  | 17556 | 0.5549          | 0.7641   |
| 0.6413        | 20.0  | 18480 | 0.5544          | 0.7654   |


### Framework versions

- Transformers 4.32.1
- Pytorch 2.0.1
- Datasets 2.12.0
- Tokenizers 0.13.2