---
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_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: 0.4140921409214092
---

<!-- 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_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: 1.7941
- Accuracy: 0.4141

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 2.4306        | 1.0   | 923   | 2.4407          | 0.2095   |
| 2.409         | 2.0   | 1846  | 2.3053          | 0.2534   |
| 2.2629        | 3.0   | 2769  | 2.2093          | 0.2808   |
| 2.1047        | 4.0   | 3692  | 2.1337          | 0.3      |
| 2.0899        | 5.0   | 4615  | 2.0657          | 0.3271   |
| 2.0152        | 6.0   | 5538  | 2.0140          | 0.3350   |
| 2.1479        | 7.0   | 6461  | 1.9759          | 0.3439   |
| 2.0267        | 8.0   | 7384  | 1.9443          | 0.3607   |
| 2.0062        | 9.0   | 8307  | 1.9180          | 0.3675   |
| 1.9883        | 10.0  | 9230  | 1.8909          | 0.3770   |
| 1.8727        | 11.0  | 10153 | 1.8694          | 0.3875   |
| 1.9236        | 12.0  | 11076 | 1.8511          | 0.3919   |
| 1.9423        | 13.0  | 11999 | 1.8378          | 0.3981   |
| 1.9526        | 14.0  | 12922 | 1.8261          | 0.3965   |
| 1.8178        | 15.0  | 13845 | 1.8139          | 0.4068   |
| 1.9548        | 16.0  | 14768 | 1.8071          | 0.4041   |
| 1.8676        | 17.0  | 15691 | 1.7999          | 0.4103   |
| 1.7727        | 18.0  | 16614 | 1.7976          | 0.4144   |
| 1.7795        | 19.0  | 17537 | 1.7949          | 0.4141   |
| 1.9062        | 20.0  | 18460 | 1.7941          | 0.4141   |


### Framework versions

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