---
license: apache-2.0
base_model: microsoft/beit-large-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: Boya1_3Class_Adamax_1e4_20Epoch_Beit-large-224_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: 0.8397297297297297
---

<!-- 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_3Class_Adamax_1e4_20Epoch_Beit-large-224_fold2

This model is a fine-tuned version of [microsoft/beit-large-patch16-224](https://huggingface.co/microsoft/beit-large-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 1.6549
- Accuracy: 0.8397

## 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: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.4334        | 1.0   | 923  | 0.4261          | 0.8314   |
| 0.3478        | 2.0   | 1846 | 0.4091          | 0.8357   |
| 0.2025        | 3.0   | 2769 | 0.6347          | 0.8408   |
| 0.0819        | 4.0   | 3692 | 0.8142          | 0.8341   |
| 0.1361        | 5.0   | 4615 | 1.0819          | 0.8441   |
| 0.0324        | 6.0   | 5538 | 1.3598          | 0.8427   |
| 0.0035        | 7.0   | 6461 | 1.6238          | 0.8430   |
| 0.0           | 8.0   | 7384 | 1.6312          | 0.8405   |
| 0.0002        | 9.0   | 8307 | 1.6680          | 0.8405   |
| 0.0001        | 10.0  | 9230 | 1.6549          | 0.8397   |


### Framework versions

- Transformers 4.32.1
- Pytorch 2.0.1
- Datasets 2.12.0
- Tokenizers 0.13.2