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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-in21k
tags:
  - image-classification
  - generated_from_trainer
datasets:
  - imagefolder
metrics:
  - accuracy
model-index:
  - name: vit-large-patch16-224-in21k-dungeon-geo-morphs-0-4-30Nov24-002
    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: 0.9660714285714286

vit-large-patch16-224-in21k-dungeon-geo-morphs-0-4-30Nov24-002

This model is a fine-tuned version of google/vit-large-patch16-224-in21k on the dungeon-geo-morphs dataset. It achieves the following results on the evaluation set:

  • Loss: 0.2581
  • Accuracy: 0.9661

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: 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: 40
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Accuracy
1.517 3.9091 10 1.3386 0.6768
0.8959 7.9091 20 0.8879 0.9089
0.4053 11.9091 30 0.5939 0.9375
0.173 15.9091 40 0.4381 0.95
0.0766 19.9091 50 0.3394 0.9589
0.0395 23.9091 60 0.2854 0.9643
0.0243 27.9091 70 0.2581 0.9661
0.0186 31.9091 80 0.2486 0.9661

Framework versions

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