---
license: apache-2.0
base_model: microsoft/beit-large-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: Boya3_3Class_RMSprop_1e5_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: 0.8495434696308058
---

<!-- 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. -->

# Boya3_3Class_RMSprop_1e5_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: 1.5872
- Accuracy: 0.8495

## 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: 1e-05
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.3849        | 1.0   | 632  | 0.3967          | 0.8273   |
| 0.3194        | 2.0   | 1264 | 0.4043          | 0.8372   |
| 0.2199        | 3.0   | 1896 | 0.4423          | 0.8503   |
| 0.1532        | 4.0   | 2528 | 0.6718          | 0.8444   |
| 0.0267        | 5.0   | 3160 | 0.9647          | 0.8416   |
| 0.0853        | 6.0   | 3792 | 1.2277          | 0.8428   |
| 0.0213        | 7.0   | 4424 | 1.4343          | 0.8491   |
| 0.0008        | 8.0   | 5056 | 1.4458          | 0.8495   |
| 0.0035        | 9.0   | 5688 | 1.5300          | 0.8495   |
| 0.0003        | 10.0  | 6320 | 1.5872          | 0.8495   |


### Framework versions

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