Edit model card

swin-base-patch4-window7-224_11092024

This model is a fine-tuned version of microsoft/swin-base-patch4-window7-224 on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.5135
  • Accuracy: 0.8337

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: 0.0003
  • train_batch_size: 16
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 20

Training results

Training Loss Epoch Step Validation Loss Accuracy
1.0366 1.0 400 0.9471 0.72
0.8257 2.0 800 0.7889 0.7538
0.7119 3.0 1200 0.7232 0.7775
0.6969 4.0 1600 0.6739 0.7837
0.6487 5.0 2000 0.6371 0.7863
0.5956 6.0 2400 0.6198 0.7887
0.5604 7.0 2800 0.5941 0.8025
0.5732 8.0 3200 0.5867 0.795
0.5578 9.0 3600 0.5705 0.8025
0.5449 10.0 4000 0.5575 0.8113
0.5419 11.0 4400 0.5505 0.8213
0.5086 12.0 4800 0.5385 0.8213
0.4929 13.0 5200 0.5340 0.8213
0.4701 14.0 5600 0.5297 0.8187
0.4803 15.0 6000 0.5240 0.8225
0.4988 16.0 6400 0.5197 0.83
0.4842 17.0 6800 0.5165 0.8313
0.4917 18.0 7200 0.5148 0.8313
0.4734 19.0 7600 0.5140 0.8325
0.4714 20.0 8000 0.5135 0.8337

Framework versions

  • Transformers 4.45.2
  • Pytorch 2.4.1+cpu
  • Datasets 3.0.1
  • Tokenizers 0.20.1
Downloads last month
11
Safetensors
Model size
86.8M params
Tensor type
I64
·
F32
·
Inference Examples
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social visibility and check back later, or deploy to Inference Endpoints (dedicated) instead.

Model tree for cvmil/swin-base-patch4-window7-224-augmented

Finetuned
(50)
this model