---
license: apache-2.0
base_model: microsoft/beit-large-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: Boya2_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: 0.8628524500410621
---

<!-- 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. -->

# Boya2_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: 1.5247
- Accuracy: 0.8629

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.3762        | 1.0   | 913  | 0.3808          | 0.8420   |
| 0.3285        | 2.0   | 1826 | 0.3567          | 0.8566   |
| 0.216         | 3.0   | 2739 | 0.4224          | 0.8494   |
| 0.2451        | 4.0   | 3652 | 0.6798          | 0.8598   |
| 0.0553        | 5.0   | 4565 | 1.0822          | 0.8483   |
| 0.0017        | 6.0   | 5478 | 1.2537          | 0.8503   |
| 0.0008        | 7.0   | 6391 | 1.3944          | 0.8552   |
| 0.0002        | 8.0   | 7304 | 1.4327          | 0.8585   |
| 0.0001        | 9.0   | 8217 | 1.5474          | 0.8661   |
| 0.0           | 10.0  | 9130 | 1.5247          | 0.8629   |


### Framework versions

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