---
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_fold4
  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: 0.8427722772277227
---

<!-- 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_fold4

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: 1.6371
- Accuracy: 0.8428

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.387         | 1.0   | 632  | 0.4262          | 0.8313   |
| 0.2307        | 2.0   | 1264 | 0.4759          | 0.7952   |
| 0.175         | 3.0   | 1896 | 0.5470          | 0.8238   |
| 0.0757        | 4.0   | 2528 | 0.8287          | 0.8388   |
| 0.0394        | 5.0   | 3160 | 1.0981          | 0.8451   |
| 0.0241        | 6.0   | 3792 | 1.2962          | 0.8285   |
| 0.0403        | 7.0   | 4424 | 1.4716          | 0.8325   |
| 0.0001        | 8.0   | 5056 | 1.5920          | 0.8436   |
| 0.0035        | 9.0   | 5688 | 1.6035          | 0.8384   |
| 0.0           | 10.0  | 6320 | 1.6371          | 0.8428   |


### Framework versions

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