---
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_fold2
  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: 0.41702702702702704
---

<!-- 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_fold2

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: 1.8092
- Accuracy: 0.4170

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 2.364         | 1.0   | 923   | 2.4299          | 0.2108   |
| 2.3719        | 2.0   | 1846  | 2.2817          | 0.2649   |
| 2.2408        | 3.0   | 2769  | 2.1860          | 0.2889   |
| 2.1829        | 4.0   | 3692  | 2.1102          | 0.3143   |
| 2.0369        | 5.0   | 4615  | 2.0577          | 0.3241   |
| 2.061         | 6.0   | 5538  | 2.0066          | 0.3419   |
| 1.9167        | 7.0   | 6461  | 1.9797          | 0.3568   |
| 2.0057        | 8.0   | 7384  | 1.9411          | 0.3673   |
| 2.0098        | 9.0   | 8307  | 1.9258          | 0.3722   |
| 1.9046        | 10.0  | 9230  | 1.9019          | 0.3822   |
| 1.862         | 11.0  | 10153 | 1.8785          | 0.3922   |
| 1.8051        | 12.0  | 11076 | 1.8624          | 0.3973   |
| 1.8752        | 13.0  | 11999 | 1.8478          | 0.3981   |
| 1.9831        | 14.0  | 12922 | 1.8389          | 0.4032   |
| 1.8913        | 15.0  | 13845 | 1.8338          | 0.4051   |
| 1.9373        | 16.0  | 14768 | 1.8269          | 0.4086   |
| 1.8457        | 17.0  | 15691 | 1.8202          | 0.4089   |
| 1.7936        | 18.0  | 16614 | 1.8117          | 0.4159   |
| 1.7608        | 19.0  | 17537 | 1.8101          | 0.4168   |
| 1.9672        | 20.0  | 18460 | 1.8092          | 0.4170   |


### Framework versions

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