generated_from_trainer

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convnext-tiny-224-finetuned-brs

This model is a fine-tuned version of facebook/convnext-tiny-224 on the imagefolder dataset. It achieves the following results on the evaluation set:

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:

Training results

Training Loss Epoch Step Validation Loss Accuracy F1 Precision (ppv) Recall (sensitivity) Specificity Npv Auc
0.6766 6.25 100 0.7002 0.4706 0.5263 0.3846 0.8333 0.2727 0.75 0.5530
0.6408 12.49 200 0.6770 0.6471 0.5714 0.5 0.6667 0.6364 0.7778 0.6515
0.464 18.74 300 0.6624 0.5882 0.5882 0.4545 0.8333 0.4545 0.8333 0.6439
0.4295 24.98 400 0.6938 0.5294 0.5 0.4 0.6667 0.4545 0.7143 0.5606
0.3952 31.25 500 0.5974 0.7059 0.6154 0.5714 0.6667 0.7273 0.8 0.6970
0.1082 37.49 600 0.6163 0.6471 0.5 0.5 0.5 0.7273 0.7273 0.6136
0.1997 43.74 700 0.6155 0.7059 0.6154 0.5714 0.6667 0.7273 0.8 0.6970
0.1267 49.98 800 0.9063 0.6471 0.5714 0.5 0.6667 0.6364 0.7778 0.6515
0.1178 56.25 900 0.8672 0.7059 0.6667 0.5556 0.8333 0.6364 0.875 0.7348
0.2008 62.49 1000 0.7049 0.8235 0.7692 0.7143 0.8333 0.8182 0.9 0.8258
0.0996 68.74 1100 0.4510 0.8235 0.7692 0.7143 0.8333 0.8182 0.9 0.8258
0.0115 74.98 1200 0.7561 0.8235 0.7692 0.7143 0.8333 0.8182 0.9 0.8258
0.0177 81.25 1300 1.0400 0.7059 0.6667 0.5556 0.8333 0.6364 0.875 0.7348
0.0261 87.49 1400 0.9139 0.8235 0.7692 0.7143 0.8333 0.8182 0.9 0.8258
0.028 93.74 1500 0.7367 0.7647 0.7143 0.625 0.8333 0.7273 0.8889 0.7803
0.0056 99.98 1600 0.8667 0.8235 0.7273 0.8 0.6667 0.9091 0.8333 0.7879

Framework versions