---
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_SGD_1-e3_20Epoch_09Momentum_Beit-base-patch16_fold3
  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: 0.4291125541125541
---

<!-- 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_SGD_1-e3_20Epoch_09Momentum_Beit-base-patch16_fold3

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: 1.7764
- Accuracy: 0.4291

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 2.4699        | 1.0   | 923   | 2.4335          | 0.2140   |
| 2.3722        | 2.0   | 1846  | 2.2936          | 0.2643   |
| 2.248         | 3.0   | 2769  | 2.1974          | 0.2884   |
| 2.1383        | 4.0   | 3692  | 2.1137          | 0.3217   |
| 2.0587        | 5.0   | 4615  | 2.0507          | 0.3404   |
| 2.0732        | 6.0   | 5538  | 2.0041          | 0.3501   |
| 2.0202        | 7.0   | 6461  | 1.9644          | 0.3693   |
| 2.0361        | 8.0   | 7384  | 1.9326          | 0.3764   |
| 1.9433        | 9.0   | 8307  | 1.8973          | 0.3926   |
| 1.9102        | 10.0  | 9230  | 1.8743          | 0.3877   |
| 1.9324        | 11.0  | 10153 | 1.8539          | 0.3950   |
| 1.943         | 12.0  | 11076 | 1.8379          | 0.4061   |
| 1.8903        | 13.0  | 11999 | 1.8194          | 0.4113   |
| 1.8833        | 14.0  | 12922 | 1.8092          | 0.4172   |
| 1.8296        | 15.0  | 13845 | 1.8007          | 0.4205   |
| 1.8152        | 16.0  | 14768 | 1.7910          | 0.4256   |
| 2.0261        | 17.0  | 15691 | 1.7844          | 0.4283   |
| 1.8132        | 18.0  | 16614 | 1.7806          | 0.4283   |
| 1.8172        | 19.0  | 17537 | 1.7782          | 0.4294   |
| 1.867         | 20.0  | 18460 | 1.7764          | 0.4291   |


### Framework versions

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