---
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_fold5
  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: 0.4277190127474912
---

<!-- 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_fold5

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: 1.7637
- Accuracy: 0.4277

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 2.3338        | 1.0   | 924   | 2.4489          | 0.2086   |
| 2.3427        | 2.0   | 1848  | 2.3125          | 0.2517   |
| 2.1284        | 3.0   | 2772  | 2.2064          | 0.2853   |
| 2.0324        | 4.0   | 3696  | 2.1236          | 0.3106   |
| 1.929         | 5.0   | 4620  | 2.0514          | 0.3369   |
| 1.9691        | 6.0   | 5544  | 1.9984          | 0.3537   |
| 2.0646        | 7.0   | 6468  | 1.9525          | 0.3653   |
| 1.8686        | 8.0   | 7392  | 1.9172          | 0.3813   |
| 1.972         | 9.0   | 8316  | 1.8843          | 0.3916   |
| 2.0678        | 10.0  | 9240  | 1.8632          | 0.3973   |
| 1.8342        | 11.0  | 10164 | 1.8414          | 0.3976   |
| 1.9641        | 12.0  | 11088 | 1.8250          | 0.4057   |
| 1.6663        | 13.0  | 12012 | 1.8107          | 0.4093   |
| 1.7839        | 14.0  | 12936 | 1.7966          | 0.4193   |
| 1.7724        | 15.0  | 13860 | 1.7857          | 0.4258   |
| 1.7746        | 16.0  | 14784 | 1.7787          | 0.4245   |
| 1.9266        | 17.0  | 15708 | 1.7714          | 0.4261   |
| 1.8612        | 18.0  | 16632 | 1.7673          | 0.4280   |
| 1.7224        | 19.0  | 17556 | 1.7664          | 0.4291   |
| 1.7078        | 20.0  | 18480 | 1.7637          | 0.4277   |


### Framework versions

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