---
license: apache-2.0
base_model: microsoft/beit-large-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: Karma_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: 0.8576483672025074
---

<!-- 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_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: 1.6418
- Accuracy: 0.8576

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.3343        | 1.0   | 2466  | 0.3772          | 0.8460   |
| 0.269         | 2.0   | 4932  | 0.3610          | 0.8583   |
| 0.1499        | 3.0   | 7398  | 0.4653          | 0.8552   |
| 0.1293        | 4.0   | 9864  | 0.8042          | 0.8496   |
| 0.1824        | 5.0   | 12330 | 0.9597          | 0.8549   |
| 0.1453        | 6.0   | 14796 | 1.2832          | 0.8563   |
| 0.0537        | 7.0   | 17262 | 1.4415          | 0.8533   |
| 0.0           | 8.0   | 19728 | 1.6006          | 0.8561   |
| 0.0           | 9.0   | 22194 | 1.6244          | 0.8587   |
| 0.0           | 10.0  | 24660 | 1.6418          | 0.8576   |


### Framework versions

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