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swinv2-small-patch4-window8-256-finetuned-eurosat

This model is a fine-tuned version of microsoft/swinv2-small-patch4-window8-256 on the food101 dataset. It achieves the following results on the evaluation set:

  • Loss: 0.4063
  • Accuracy: 0.8847

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: 3

Training results

Training Loss Epoch Step Validation Loss Accuracy
1.3521 1.0 592 0.7233 0.7967
0.9887 2.0 1184 0.5211 0.8519
0.845 3.0 1776 0.4063 0.8847

Framework versions

  • Transformers 4.32.1
  • Pytorch 2.0.1+cu118
  • Datasets 2.14.4
  • Tokenizers 0.13.3
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Dataset used to train lu5/swinv2-small-patch4-window8-256-finetuned-eurosat

Evaluation results