NMM_Classification_base_V10
This model is a fine-tuned version of microsoft/swin-base-patch4-window7-224-in22k on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 0.4066
- Accuracy: 0.8349
- Auc Overall: 0.9379
- Auc Class 0: 0.9614
- Auc Class 1: 0.9315
- Auc Class 2: 0.9207
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: 7
Training results
Framework versions
- Transformers 4.44.2
- Pytorch 1.13.1+cu117
- Datasets 2.20.0
- Tokenizers 0.19.1
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Model tree for djbp/NMM_Classification_base_V10
Base model
microsoft/swin-base-patch4-window7-224-in22kEvaluation results
- Accuracy on imagefoldervalidation set self-reported0.835