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portrait_cosu_exp3

This model is a fine-tuned version of NekoFi/content-manage-exp2 on the imagefolder dataset. It achieves the following results on the evaluation set:

  • Loss: 0.2524
  • Accuracy: 0.9149
  • Precision: 0.9190
  • Recall: 0.9149
  • F1: 0.9153
  • Confusion Matrix: [[19, 1], [3, 24]]

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: 4

Training results

Training Loss Epoch Step Validation Loss Accuracy Precision Recall F1 Confusion Matrix
No log 0.9231 6 0.2921 0.8511 0.8527 0.8511 0.8515 [[17, 3], [4, 23]]
0.5415 2.0 13 0.2564 0.9362 0.9426 0.9362 0.9353 [[17, 3], [0, 27]]
0.5415 2.9231 19 0.3605 0.8723 0.8864 0.8723 0.8730 [[19, 1], [5, 22]]
0.378 3.6923 24 0.2524 0.9149 0.9190 0.9149 0.9153 [[19, 1], [3, 24]]

Framework versions

  • Transformers 4.40.2
  • Pytorch 2.2.1+cu121
  • Datasets 2.19.1
  • Tokenizers 0.19.1
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Evaluation results