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beit-base-patch16-224-pt22k-ft22k-finetuned-ind-17-imbalanced-aadhaarmask

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beit-base-patch16-224-pt22k-ft22k-finetuned-ind-17-imbalanced-aadhaarmask

This model is a fine-tuned version of microsoft/beit-base-patch16-224-pt22k-ft22k on the imagefolder dataset. It achieves the following results on the evaluation set:

  • Loss: 0.3480
  • Accuracy: 0.8450
  • Recall: 0.8450
  • F1: 0.8442
  • Precision: 0.8494

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: 8
  • seed: 42
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 32
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_ratio: 0.1
  • num_epochs: 10

Training results

Training Loss Epoch Step Validation Loss Accuracy Recall F1 Precision
0.5859 0.9974 293 0.6117 0.8114 0.8114 0.7891 0.8139
0.5281 1.9983 587 0.4362 0.8442 0.8442 0.8375 0.8484
0.4214 2.9991 881 0.4228 0.8438 0.8438 0.8392 0.8529
0.4221 4.0 1175 0.4121 0.8382 0.8382 0.8331 0.8495
0.4127 4.9974 1468 0.3692 0.8476 0.8476 0.8454 0.8511
0.3122 5.9983 1762 0.3741 0.8408 0.8408 0.8394 0.8462
0.3079 6.9991 2056 0.3628 0.8429 0.8429 0.8403 0.8445
0.2851 8.0 2350 0.3635 0.8412 0.8412 0.8389 0.8412
0.297 8.9974 2643 0.3407 0.8510 0.8510 0.8497 0.8545
0.2109 9.9745 2930 0.3566 0.8421 0.8421 0.8406 0.8418

Framework versions

  • Transformers 4.40.1
  • Pytorch 2.2.0a0+81ea7a4
  • Datasets 2.19.0
  • Tokenizers 0.19.1
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Model tree for Kushagra07/beit-base-patch16-224-pt22k-ft22k-finetuned-ind-17-imbalanced-aadhaarmask

Base model

microsoft/beit-base-patch16-224-pt22k-ft22k
Finetuned
(60)
this model

Evaluation results

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