---
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_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: 0.8322147651006712
---

<!-- 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_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: 1.8357
- Accuracy: 0.8322

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.4181        | 1.0   | 631  | 0.4865          | 0.7722   |
| 0.3391        | 2.0   | 1262 | 0.4494          | 0.8314   |
| 0.1276        | 3.0   | 1893 | 0.5148          | 0.8393   |
| 0.1436        | 4.0   | 2524 | 0.7474          | 0.8302   |
| 0.1404        | 5.0   | 3155 | 1.1243          | 0.8287   |
| 0.0742        | 6.0   | 3786 | 1.4178          | 0.8401   |
| 0.0155        | 7.0   | 4417 | 1.6465          | 0.8247   |
| 0.0           | 8.0   | 5048 | 1.7427          | 0.8239   |
| 0.0           | 9.0   | 5679 | 1.8000          | 0.8346   |
| 0.0           | 10.0  | 6310 | 1.8357          | 0.8322   |


### Framework versions

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