---
license: apache-2.0
base_model: microsoft/beit-large-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: Karma_3Class_3Class_Adamax_1e4_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: 0.8534020827014458
---

<!-- 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. -->

# Karma_3Class_3Class_Adamax_1e4_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: 1.5433
- Accuracy: 0.8534

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.3595        | 1.0   | 2466  | 0.4309          | 0.8251   |
| 0.3101        | 2.0   | 4932  | 0.3865          | 0.8447   |
| 0.1826        | 3.0   | 7398  | 0.4588          | 0.8485   |
| 0.1658        | 4.0   | 9864  | 0.5997          | 0.8504   |
| 0.1373        | 5.0   | 12330 | 0.8549          | 0.8498   |
| 0.0639        | 6.0   | 14796 | 1.1026          | 0.8527   |
| 0.0234        | 7.0   | 17262 | 1.2762          | 0.8538   |
| 0.0001        | 8.0   | 19728 | 1.4347          | 0.8547   |
| 0.0           | 9.0   | 22194 | 1.5139          | 0.8518   |
| 0.0002        | 10.0  | 24660 | 1.5433          | 0.8534   |


### Framework versions

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