---
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_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: 0.8513252767340307
---

<!-- 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_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: 1.6695
- Accuracy: 0.8513

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.3814        | 1.0   | 2469  | 0.4224          | 0.8261   |
| 0.3149        | 2.0   | 4938  | 0.3974          | 0.8373   |
| 0.229         | 3.0   | 7407  | 0.4573          | 0.8494   |
| 0.1553        | 4.0   | 9876  | 0.6588          | 0.8355   |
| 0.0159        | 5.0   | 12345 | 0.9590          | 0.8493   |
| 0.055         | 6.0   | 14814 | 1.1582          | 0.8487   |
| 0.0266        | 7.0   | 17283 | 1.2517          | 0.8498   |
| 0.0003        | 8.0   | 19752 | 1.5699          | 0.8506   |
| 0.0           | 9.0   | 22221 | 1.6357          | 0.8514   |
| 0.0           | 10.0  | 24690 | 1.6695          | 0.8513   |


### Framework versions

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