griffio's picture
Model save
1c14c56 verified
|
raw
history blame
2.33 kB
metadata
library_name: transformers
license: apache-2.0
base_model: google/vit-large-patch16-224
tags:
  - generated_from_trainer
datasets:
  - imagefolder
metrics:
  - accuracy
model-index:
  - name: vit-large-patch16-224-dungeon-geo-morphs-0-4-26Nov24-001
    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: 0.9938775510204082

vit-large-patch16-224-dungeon-geo-morphs-0-4-26Nov24-001

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

  • Loss: 0.0282
  • Accuracy: 0.9939

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
1.2849 4.4444 10 0.6545 0.8837
0.2089 8.8889 20 0.1889 0.9694
0.0278 13.3333 30 0.0619 0.9878
0.0034 17.7778 40 0.0349 0.9918
0.0012 22.2222 50 0.0282 0.9918
0.0008 26.6667 60 0.0282 0.9939

Framework versions

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