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: nan
- Accuracy: 0.0630
- 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+git74cd574
- Datasets 3.1.0
- Tokenizers 0.20.1
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Base model
google/vit-base-patch16-224-in21k