---
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_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: 0.6532717893021993
---

<!-- 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_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: 3.0645
- Accuracy: 0.6533

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 1.1014        | 1.0   | 924   | 1.1155          | 0.6131   |
| 0.917         | 2.0   | 1848  | 1.0767          | 0.6242   |
| 0.7533        | 3.0   | 2772  | 1.0565          | 0.6473   |
| 0.493         | 4.0   | 3696  | 1.1952          | 0.6530   |
| 0.482         | 5.0   | 4620  | 1.3688          | 0.6473   |
| 0.1989        | 6.0   | 5544  | 1.6284          | 0.6435   |
| 0.1622        | 7.0   | 6468  | 2.0114          | 0.6373   |
| 0.0666        | 8.0   | 7392  | 2.2124          | 0.6541   |
| 0.0417        | 9.0   | 8316  | 2.4424          | 0.6389   |
| 0.0196        | 10.0  | 9240  | 2.5614          | 0.6397   |
| 0.0323        | 11.0  | 10164 | 2.8070          | 0.6443   |
| 0.0014        | 12.0  | 11088 | 2.8503          | 0.6506   |
| 0.001         | 13.0  | 12012 | 2.8885          | 0.6497   |
| 0.0706        | 14.0  | 12936 | 3.0224          | 0.6462   |
| 0.0003        | 15.0  | 13860 | 3.0064          | 0.6465   |
| 0.0013        | 16.0  | 14784 | 3.0115          | 0.6552   |
| 0.0316        | 17.0  | 15708 | 3.0514          | 0.6563   |
| 0.0002        | 18.0  | 16632 | 3.0348          | 0.6568   |
| 0.0           | 19.0  | 17556 | 3.0737          | 0.6508   |
| 0.0494        | 20.0  | 18480 | 3.0645          | 0.6533   |


### Framework versions

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