---
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_fold3
  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: 0.8452742359846185
---

<!-- 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_fold3

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: 1.6691
- Accuracy: 0.8453

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.4597        | 1.0   | 2467  | 0.3981          | 0.8379   |
| 0.3536        | 2.0   | 4934  | 0.3996          | 0.8368   |
| 0.1795        | 3.0   | 7401  | 0.4872          | 0.8467   |
| 0.1625        | 4.0   | 9868  | 0.6122          | 0.8475   |
| 0.1107        | 5.0   | 12335 | 0.9789          | 0.8460   |
| 0.0003        | 6.0   | 14802 | 1.0818          | 0.8494   |
| 0.0149        | 7.0   | 17269 | 1.4834          | 0.8465   |
| 0.0           | 8.0   | 19736 | 1.5090          | 0.8474   |
| 0.0           | 9.0   | 22203 | 1.5763          | 0.8462   |
| 0.001         | 10.0  | 24670 | 1.6691          | 0.8453   |


### Framework versions

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