---
library_name: peft
license: apache-2.0
base_model: google/vit-large-patch16-224
tags:
- image-classification
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: vit-large-patch16-224-testing-dungeons-lora-23Nov24-009
  results:
  - task:
      type: image-classification
      name: Image Classification
    dataset:
      name: rotated_maps
      type: imagefolder
      config: default
      split: validation
      args: default
    metrics:
    - type: accuracy
      value: 0.9629629629629629
      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-testing-dungeons-lora-23Nov24-009

This model is a fine-tuned version of [google/vit-large-patch16-224](https://huggingface.co/google/vit-large-patch16-224) on the rotated_maps dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1605
- Accuracy: 0.9630

## 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
- num_epochs: 12
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| No log        | 0.6667 | 1    | 1.4611          | 0.2963   |
| No log        | 2.0    | 3    | 1.0087          | 0.5185   |
| No log        | 2.6667 | 4    | 1.5508          | 0.4074   |
| No log        | 4.0    | 6    | 0.4546          | 0.8889   |
| No log        | 4.6667 | 7    | 0.4480          | 0.8148   |
| No log        | 6.0    | 9    | 0.2657          | 0.8889   |
| 0.8959        | 6.6667 | 10   | 0.2433          | 0.8889   |
| 0.8959        | 8.0    | 12   | 0.1605          | 0.9630   |


### Framework versions

- PEFT 0.13.2
- Transformers 4.46.2
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3