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:

  • eval_loss: 2.7757
  • eval_model_preparation_time: 0.0119
  • eval_accuracy: 0.0567
  • eval_runtime: 362.8091
  • eval_samples_per_second: 132.301
  • eval_steps_per_second: 2.067
  • memory_allocated (GB): 0.79
  • max_memory_allocated (GB): 0.87
  • total_memory_available (GB): 94.62
  • step: 0

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

Framework versions

  • Transformers 4.45.2
  • Pytorch 2.4.0a0+git74cd574
  • Datasets 3.0.2
  • Tokenizers 0.20.1
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