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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-0-4-30Nov24-004
    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: 0.9625

vit-large-patch16-224-in21k-dungeon-geo-morphs-0-4-30Nov24-004

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: 0.1275
  • Accuracy: 0.9625

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: 40
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Accuracy
1.3834 3.9091 10 1.1055 0.7929
0.5606 7.9091 20 0.5141 0.9286
0.13 11.9091 30 0.2629 0.9518
0.0283 15.9091 40 0.1654 0.9464
0.0082 19.9091 50 0.1352 0.9554
0.0043 23.9091 60 0.1337 0.9589
0.0033 27.9091 70 0.1257 0.9607
0.0029 31.9091 80 0.1275 0.9625

Framework versions

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