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dungeon-geo-morphs
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metadata
library_name: transformers
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-new-dungeon-geo-morphs-009
    results:
      - task:
          name: Image Classification
          type: image-classification
        dataset:
          name: dungeon-geo-morphs
          type: imagefolder
          config: default
          split: validation
          args: default
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.96

vit-large-patch16-224-new-dungeon-geo-morphs-009

This model is a fine-tuned version of google/vit-large-patch16-224 on the dungeon-geo-morphs dataset. It achieves the following results on the evaluation set:

  • Loss: 0.0997
  • Accuracy: 0.96

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: 2e-05
  • 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: 30
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Accuracy
1.1702 4.4444 10 0.5499 0.94
0.1925 8.8889 20 0.1645 0.94
0.0112 13.3333 30 0.0997 0.96
0.0011 17.7778 40 0.1255 0.96
0.0005 22.2222 50 0.1313 0.96
0.0004 26.6667 60 0.1238 0.96

Framework versions

  • Transformers 4.46.2
  • Pytorch 2.5.1+cu121
  • Datasets 3.1.0
  • Tokenizers 0.20.3