---
library_name: peft
license: apache-2.0
base_model: google/vit-large-patch16-224-in21k
tags:
- image-classification
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: vit-large-patch16-224-in21k-testing-dungeons-lora-27Dec24-0001
  results:
  - task:
      type: image-classification
      name: Image Classification
    dataset:
      name: rotated_maps
      type: imagefolder
      config: default
      split: validation
      args: default
    metrics:
    - type: accuracy
      value: 0.9607142857142857
      name: Accuracy
---

<!-- 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. -->

# vit-large-patch16-224-in21k-testing-dungeons-lora-27Dec24-0001

This model is a fine-tuned version of [google/vit-large-patch16-224-in21k](https://huggingface.co/google/vit-large-patch16-224-in21k) on the rotated_maps dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1076
- Accuracy: 0.9607

## 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: 0.005
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 12
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Accuracy |
|:-------------:|:-------:|:----:|:---------------:|:--------:|
| No log        | 0.7273  | 2    | 1.5502          | 0.2946   |
| No log        | 1.7273  | 4    | 1.1408          | 0.6696   |
| No log        | 2.7273  | 6    | 1.0113          | 0.6036   |
| No log        | 3.7273  | 8    | 0.6030          | 0.8411   |
| 5.1081        | 4.7273  | 10   | 0.4665          | 0.8625   |
| 5.1081        | 5.7273  | 12   | 0.4145          | 0.8643   |
| 5.1081        | 6.7273  | 14   | 0.2846          | 0.9107   |
| 5.1081        | 7.7273  | 16   | 0.2386          | 0.9125   |
| 5.1081        | 8.7273  | 18   | 0.1564          | 0.9554   |
| 0.7653        | 9.7273  | 20   | 0.1178          | 0.9679   |
| 0.7653        | 10.7273 | 22   | 0.1241          | 0.9536   |
| 0.7653        | 11.7273 | 24   | 0.1076          | 0.9607   |


### Framework versions

- PEFT 0.14.0
- Transformers 4.47.1
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0