---
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_fold4
  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: 0.8233062330623306
---

<!-- 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_fold4

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: 1.8083
- Accuracy: 0.8233

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.3492        | 1.0   | 923   | 0.4516          | 0.8087   |
| 0.3947        | 2.0   | 1846  | 0.4372          | 0.8144   |
| 0.3321        | 3.0   | 2769  | 0.4856          | 0.8220   |
| 0.1372        | 4.0   | 3692  | 0.6093          | 0.8271   |
| 0.2202        | 5.0   | 4615  | 0.8876          | 0.8184   |
| 0.0611        | 6.0   | 5538  | 1.1112          | 0.8222   |
| 0.0654        | 7.0   | 6461  | 1.2516          | 0.8241   |
| 0.0494        | 8.0   | 7384  | 1.5011          | 0.8209   |
| 0.0614        | 9.0   | 8307  | 1.3879          | 0.8190   |
| 0.1723        | 10.0  | 9230  | 1.5852          | 0.8160   |
| 0.0314        | 11.0  | 10153 | 1.7058          | 0.8209   |
| 0.006         | 12.0  | 11076 | 1.7427          | 0.8233   |
| 0.0603        | 13.0  | 11999 | 1.6775          | 0.8206   |
| 0.0734        | 14.0  | 12922 | 1.7302          | 0.8257   |
| 0.0185        | 15.0  | 13845 | 1.7895          | 0.8236   |
| 0.0006        | 16.0  | 14768 | 1.7889          | 0.8220   |
| 0.0006        | 17.0  | 15691 | 1.8447          | 0.8198   |
| 0.0003        | 18.0  | 16614 | 1.8183          | 0.8184   |
| 0.0002        | 19.0  | 17537 | 1.8137          | 0.8176   |
| 0.0           | 20.0  | 18460 | 1.8083          | 0.8233   |


### Framework versions

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