---
license: apache-2.0
base_model: microsoft/beit-large-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: Boya1_3Class_SGD_1e3_20Epoch_Beit-large-224_fold1
  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: 0.7360847135487374
---

<!-- 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_SGD_1e3_20Epoch_Beit-large-224_fold1

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: 0.6426
- Accuracy: 0.7361

## 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: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.8408        | 1.0   | 924  | 0.9037          | 0.6155   |
| 0.8244        | 2.0   | 1848 | 0.7895          | 0.6715   |
| 0.8238        | 3.0   | 2772 | 0.7327          | 0.6951   |
| 0.6266        | 4.0   | 3696 | 0.6993          | 0.7092   |
| 0.7355        | 5.0   | 4620 | 0.6767          | 0.7220   |
| 0.6356        | 6.0   | 5544 | 0.6627          | 0.7288   |
| 0.6111        | 7.0   | 6468 | 0.6531          | 0.7317   |
| 0.6432        | 8.0   | 7392 | 0.6463          | 0.7355   |
| 0.5597        | 9.0   | 8316 | 0.6435          | 0.7353   |
| 0.7957        | 10.0  | 9240 | 0.6426          | 0.7361   |


### Framework versions

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