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End of training
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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: Train-Augmentation-V2-swinv2-base
    results: []

Train-Augmentation-V2-swinv2-base

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: 0.9822
  • Accuracy: 0.8459

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: 16
  • eval_batch_size: 16
  • seed: 42
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 64
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_ratio: 0.1
  • num_epochs: 15

Training results

Training Loss Epoch Step Validation Loss Accuracy
0.5894 0.99 109 0.7123 0.7481
0.2772 2.0 219 0.6394 0.7970
0.1863 3.0 329 0.7819 0.7669
0.0925 4.0 439 0.7062 0.8083
0.0461 4.99 548 0.8637 0.8120
0.0427 6.0 658 0.9080 0.7970
0.043 7.0 768 1.0747 0.8045
0.0074 8.0 878 0.9019 0.8421
0.0169 8.99 987 0.9099 0.8459
0.015 10.0 1097 0.9512 0.8647
0.0022 11.0 1207 1.0051 0.8609
0.0081 12.0 1317 1.0061 0.8308
0.0013 12.99 1426 0.9844 0.8534
0.0037 14.0 1536 0.9864 0.8459
0.0002 14.9 1635 0.9822 0.8459

Framework versions

  • Transformers 4.39.3
  • Pytorch 2.1.2
  • Datasets 2.19.1
  • Tokenizers 0.15.2