---
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_3Class_RMSprop_1-e5_20Epoch_Beit-base-patch16_fold3
  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: 0.8222402597402597
---

<!-- 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_RMSprop_1-e5_20Epoch_Beit-base-patch16_fold3

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: 1.8476
- Accuracy: 0.8222

## 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: 20

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.4509        | 1.0   | 923   | 0.4494          | 0.8149   |
| 0.3482        | 2.0   | 1846  | 0.4215          | 0.8328   |
| 0.2766        | 3.0   | 2769  | 0.4845          | 0.8241   |
| 0.1282        | 4.0   | 3692  | 0.6763          | 0.8333   |
| 0.0823        | 5.0   | 4615  | 0.8609          | 0.8252   |
| 0.2362        | 6.0   | 5538  | 1.1571          | 0.8163   |
| 0.0242        | 7.0   | 6461  | 1.3157          | 0.8203   |
| 0.0078        | 8.0   | 7384  | 1.5067          | 0.8063   |
| 0.0045        | 9.0   | 8307  | 1.5694          | 0.8182   |
| 0.0161        | 10.0  | 9230  | 1.6636          | 0.8168   |
| 0.005         | 11.0  | 10153 | 1.7056          | 0.8185   |
| 0.0057        | 12.0  | 11076 | 1.6400          | 0.8222   |
| 0.0001        | 13.0  | 11999 | 1.7600          | 0.8258   |
| 0.0671        | 14.0  | 12922 | 1.8091          | 0.8241   |
| 0.0041        | 15.0  | 13845 | 1.8050          | 0.8225   |
| 0.0           | 16.0  | 14768 | 1.8120          | 0.8222   |
| 0.0556        | 17.0  | 15691 | 1.8242          | 0.8212   |
| 0.0           | 18.0  | 16614 | 1.8578          | 0.8214   |
| 0.0           | 19.0  | 17537 | 1.8441          | 0.8217   |
| 0.0099        | 20.0  | 18460 | 1.8476          | 0.8222   |


### Framework versions

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