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metadata
license: apache-2.0
base_model: microsoft/swinv2-base-patch4-window12to16-192to256-22kto1k-ft
tags:
  - generated_from_trainer
metrics:
  - accuracy
model-index:
  - name: 1_M_cards-swinv2-base-patch4-window12to16-192to256-22kto1k-ft-finetuned-v3
    results: []

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1_M_cards-swinv2-base-patch4-window12to16-192to256-22kto1k-ft-finetuned-v3

This model is a fine-tuned version of microsoft/swinv2-base-patch4-window12to16-192to256-22kto1k-ft on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 1.1701
  • Accuracy: 0.5118

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: 128
  • eval_batch_size: 128
  • seed: 42
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 512
  • 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
1.3156 0.9995 1633 1.2976 0.4477
1.2943 1.9997 3267 1.2443 0.4668
1.2411 2.9998 4901 1.2229 0.4787
1.2368 4.0 6535 1.1967 0.4901
1.1973 4.9995 8168 1.1910 0.4927
1.2124 5.9997 9802 1.1811 0.4989
1.1753 6.9998 11436 1.1685 0.5062
1.1554 8.0 13070 1.1681 0.5080
1.1279 8.9995 14703 1.1685 0.5100
1.1121 9.9954 16330 1.1701 0.5118

Framework versions

  • Transformers 4.41.0
  • Pytorch 2.0.1+cu117
  • Datasets 2.19.1
  • Tokenizers 0.19.1