---
license: apache-2.0
base_model: microsoft/beit-base-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: Karma_3Class_RMSprop_1-e5_10Epoch_Beit-base-patch16_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: 0.843291881508442
---

<!-- 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_RMSprop_1-e5_10Epoch_Beit-base-patch16_fold2

This model is a fine-tuned version of [microsoft/beit-base-patch16-224](https://huggingface.co/microsoft/beit-base-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 1.4322
- Accuracy: 0.8433

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.3441        | 1.0   | 2466  | 0.3930          | 0.8392   |
| 0.3299        | 2.0   | 4932  | 0.3836          | 0.8474   |
| 0.2436        | 3.0   | 7398  | 0.4043          | 0.8499   |
| 0.2235        | 4.0   | 9864  | 0.5186          | 0.8408   |
| 0.178         | 5.0   | 12330 | 0.6810          | 0.8485   |
| 0.1455        | 6.0   | 14796 | 0.8839          | 0.8442   |
| 0.1409        | 7.0   | 17262 | 1.1134          | 0.8424   |
| 0.181         | 8.0   | 19728 | 1.3633          | 0.8364   |
| 0.0965        | 9.0   | 22194 | 1.4369          | 0.8388   |
| 0.0314        | 10.0  | 24660 | 1.4322          | 0.8433   |


### Framework versions

- Transformers 4.35.0
- Pytorch 2.1.0
- Datasets 2.14.6
- Tokenizers 0.14.1