metadata

library_name: transformers
license: apache-2.0
base_model: google/vit-large-patch16-224-in21k
tags:
  - generated_from_trainer
datasets:
  - imagefolder
metrics:
  - accuracy
model-index:
  - name: vit-large-patch16-224-in21k-dungeon-geo-morphs-denoised-04Dec24-002
    results:
      - task:
          name: Image Classification
          type: image-classification
        dataset:
          name: imagefolder
          type: imagefolder
          config: default
          split: validation
          args: default
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.9656565656565657

vit-large-patch16-224-in21k-dungeon-geo-morphs-denoised-04Dec24-002

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

Loss: 0.1107
Accuracy: 0.9657

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
1.4876	4.0	10	1.1611	0.6545
0.6201	8.0	20	0.5442	0.9152
0.1543	12.0	30	0.2724	0.9556
0.0344	16.0	40	0.1593	0.9636
0.0095	20.0	50	0.1314	0.9657
0.0047	24.0	60	0.1091	0.9657
0.0033	28.0	70	0.1139	0.9636
0.0029	32.0	80	0.1107	0.9657

Framework versions

Transformers 4.46.2
Pytorch 2.5.1+cu121
Datasets 3.1.0
Tokenizers 0.20.3