debajyotidasgupta's picture
Model save
180ac42 verified
metadata
license: apache-2.0
base_model: microsoft/swin-base-patch4-window7-224-in22k
tags:
  - generated_from_trainer
datasets:
  - imagefolder
metrics:
  - f1
model-index:
  - name: swin-base-patch4-window7-224-in22k
    results:
      - task:
          name: Image Classification
          type: image-classification
        dataset:
          name: imagefolder
          type: imagefolder
          config: default
          split: train
          args: default
        metrics:
          - name: F1
            type: f1
            value: 0.976218332192814

swin-base-patch4-window7-224-in22k

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: 0.0117
  • F1: 0.9762

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: 32
  • eval_batch_size: 32
  • seed: 42
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 128
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_ratio: 0.1
  • num_epochs: 10

Training results

Training Loss Epoch Step Validation Loss F1
0.0575 0.99 50 0.0560 0.9257
0.0561 2.0 101 0.0359 0.9475
0.027 2.99 151 0.0212 0.9643
0.0236 4.0 202 0.0145 0.9737
0.0256 4.99 252 0.0269 0.9503
0.0226 6.0 303 0.0123 0.9762
0.0265 6.99 353 0.0135 0.9731
0.0168 8.0 404 0.0098 0.9824
0.0074 8.99 454 0.0172 0.9700
0.0125 9.9 500 0.0117 0.9762

Framework versions

  • Transformers 4.37.2
  • Pytorch 1.12.1+cu102
  • Datasets 2.16.1
  • Tokenizers 0.15.1