vit-base-patch16-224-in21k

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

  • Loss: 0.4223
  • Accuracy: 0.8788
  • Memory Allocated (gb): 1.49
  • Max Memory Allocated (gb): 2.1
  • Total Memory Available (gb): 126.62

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: 5e-05
  • train_batch_size: 8
  • eval_batch_size: 64
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-06
  • lr_scheduler_type: linear
  • num_epochs: 3.0

Training results

Framework versions

  • Transformers 4.45.2
  • Pytorch 2.4.0a0+git12138a8
  • Datasets 3.1.0
  • Tokenizers 0.20.3
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