convnextv2-tiny-1k-224-finetuned-crop-neckline

This model is a fine-tuned version of facebook/convnextv2-tiny-1k-224 on the imagefolder dataset. It achieves the following results on the evaluation set:

  • Loss: 0.6160
  • Accuracy: 0.8095
  • Precision: 0.8101

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: 10
  • eval_batch_size: 4
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 100

Training results

Training Loss Epoch Step Validation Loss Accuracy Precision
No log 1.0 84 1.4226 0.5619 0.5870
No log 2.0 168 1.1924 0.5619 0.5663
No log 3.0 252 0.9542 0.6952 0.7317
No log 4.0 336 0.8255 0.7143 0.7224
No log 5.0 420 0.7614 0.7190 0.7378
1.1937 6.0 504 0.7303 0.7381 0.7454
1.1937 7.0 588 0.6770 0.7667 0.7772
1.1937 8.0 672 0.6849 0.7667 0.7748
1.1937 9.0 756 0.6720 0.7381 0.7532
1.1937 10.0 840 0.7036 0.7286 0.7429
1.1937 11.0 924 0.6752 0.7619 0.7827
0.6846 12.0 1008 0.6399 0.7810 0.7860
0.6846 13.0 1092 0.6860 0.7381 0.7553
0.6846 14.0 1176 0.6827 0.7476 0.7644
0.6846 15.0 1260 0.6160 0.8095 0.8101
0.6846 16.0 1344 0.7032 0.7619 0.7695
0.6846 17.0 1428 0.6916 0.8048 0.8197
0.5051 18.0 1512 0.7070 0.7810 0.7891

Framework versions

  • Transformers 4.44.0
  • Pytorch 2.4.0
  • Datasets 2.21.0
  • Tokenizers 0.19.1
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Evaluation results