---
license: apache-2.0
base_model: microsoft/beit-large-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: Boya2_3Class_Adamax_1e4_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: 0.8595336076817558
---

<!-- 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_Adamax_1e4_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: 1.4832
- Accuracy: 0.8595

## 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: 0.0001
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.3205        | 1.0   | 914  | 0.4126          | 0.8335   |
| 0.3896        | 2.0   | 1828 | 0.3489          | 0.8595   |
| 0.2815        | 3.0   | 2742 | 0.4941          | 0.8250   |
| 0.0932        | 4.0   | 3656 | 0.8851          | 0.8431   |
| 0.0061        | 5.0   | 4570 | 1.0518          | 0.8527   |
| 0.0199        | 6.0   | 5484 | 1.2561          | 0.8529   |
| 0.0725        | 7.0   | 6398 | 1.4266          | 0.8565   |
| 0.0           | 8.0   | 7312 | 1.4824          | 0.8543   |
| 0.0           | 9.0   | 8226 | 1.4678          | 0.8579   |
| 0.0           | 10.0  | 9140 | 1.4832          | 0.8595   |


### Framework versions

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