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metadata
license: apache-2.0
base_model: microsoft/swinv2-large-patch4-window12-192-22k
tags:
  - generated_from_trainer
metrics:
  - accuracy
model-index:
  - name: 0.50-200Train-100Test-swinv2-large
    results: []

0.50-200Train-100Test-swinv2-large

This model is a fine-tuned version of microsoft/swinv2-large-patch4-window12-192-22k on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.7669
  • Accuracy: 0.8233

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: 20

Training results

Training Loss Epoch Step Validation Loss Accuracy
2.4602 0.9825 14 1.7254 0.4318
1.7105 1.9649 28 0.8579 0.7047
0.6096 2.9474 42 0.7268 0.7562
0.3983 4.0 57 0.6706 0.7852
0.1083 4.9825 71 0.7051 0.7897
0.0952 5.9649 85 0.8423 0.7696
0.1106 6.9474 99 0.6406 0.8121
0.0357 8.0 114 0.8410 0.7897
0.0522 8.9825 128 0.8197 0.7987
0.0274 9.9649 142 0.8788 0.8098
0.0203 10.9474 156 0.8037 0.8233
0.0361 12.0 171 0.7932 0.8076
0.0204 12.9825 185 0.7503 0.8210
0.0165 13.9649 199 0.7416 0.8098
0.0129 14.9474 213 0.8474 0.8277
0.0062 16.0 228 0.7788 0.8233
0.0028 16.9825 242 0.7687 0.8255
0.001 17.9649 256 0.7730 0.8255
0.0019 18.9474 270 0.7681 0.8255
0.0014 19.6491 280 0.7669 0.8233

Framework versions

  • Transformers 4.41.2
  • Pytorch 2.1.2
  • Datasets 2.19.2
  • Tokenizers 0.19.1