amunchet_rorshark-vit-base

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license: apache-2.0 base_model: google/vit-base-patch16-224-in21k tags:

• image-classification
• vision
• generated_from_trainer datasets:
• imagefolder metrics:
• accuracy model-index:
• name: rorshark-vit-base results:
  • task: name: Image Classification type: image-classification dataset: name: imagefolder type: imagefolder config: default split: train args: default metrics:
    • name: Accuracy type: accuracy value: 0.9922928709055877

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rorshark-vit-base

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

• Loss: 0.0393
• Accuracy: 0.9923

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: 1337
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 5.0

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.0597	1.0	368	0.0546	0.9865
0.2009	2.0	736	0.0531	0.9865
0.0114	3.0	1104	0.0418	0.9904
0.0998	4.0	1472	0.0425	0.9904
0.1244	5.0	1840	0.0393	0.9923

Framework versions

• Transformers 4.36.0.dev0
• Pytorch 2.1.1+cu118
• Datasets 2.15.0
• Tokenizers 0.15.0