---
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_fold4
  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: 0.8525537089582489
---

<!-- 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_fold4

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: 1.7123
- Accuracy: 0.8526

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.3832        | 1.0   | 2468  | 0.3649          | 0.8517   |
| 0.2748        | 2.0   | 4936  | 0.4155          | 0.8512   |
| 0.2186        | 3.0   | 7404  | 0.4719          | 0.8499   |
| 0.0708        | 4.0   | 9872  | 0.7558          | 0.8559   |
| 0.0071        | 5.0   | 12340 | 1.1190          | 0.8519   |
| 0.0188        | 6.0   | 14808 | 1.3945          | 0.8457   |
| 0.0003        | 7.0   | 17276 | 1.5102          | 0.8560   |
| 0.0           | 8.0   | 19744 | 1.6102          | 0.8568   |
| 0.0664        | 9.0   | 22212 | 1.7280          | 0.8513   |
| 0.0001        | 10.0  | 24680 | 1.7123          | 0.8526   |


### Framework versions

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