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metadata
license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - food101
metrics:
  - accuracy
base_model: microsoft/swin-base-patch4-window7-224
model-index:
  - name: swin-finetuned-food101
    results:
      - task:
          type: image-classification
          name: Image Classification
        dataset:
          name: food101
          type: food101
          args: default
        metrics:
          - type: accuracy
            value: 0.9210297029702971
            name: Accuracy
      - task:
          type: image-classification
          name: Image Classification
        dataset:
          name: food101
          type: food101
          config: default
          split: validation
        metrics:
          - type: accuracy
            value: 0.9135841584158416
            name: Accuracy
            verified: true
          - type: precision
            value: 0.9151645786633058
            name: Precision Macro
            verified: true
          - type: precision
            value: 0.9135841584158416
            name: Precision Micro
            verified: true
          - type: precision
            value: 0.915164578663306
            name: Precision Weighted
            verified: true
          - type: recall
            value: 0.9135841584158414
            name: Recall Macro
            verified: true
          - type: recall
            value: 0.9135841584158416
            name: Recall Micro
            verified: true
          - type: recall
            value: 0.9135841584158416
            name: Recall Weighted
            verified: true
          - type: f1
            value: 0.9138785016966742
            name: F1 Macro
            verified: true
          - type: f1
            value: 0.9135841584158415
            name: F1 Micro
            verified: true
          - type: f1
            value: 0.9138785016966743
            name: F1 Weighted
            verified: true
          - type: loss
            value: 0.30761435627937317
            name: loss
            verified: true

swin-finetuned-food101

This model is a fine-tuned version of microsoft/swin-base-patch4-window7-224 on the food101 dataset. It achieves the following results on the evaluation set:

  • Loss: 0.2772
  • Accuracy: 0.9210

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: 3

Training results

Training Loss Epoch Step Validation Loss Accuracy
0.5077 1.0 1183 0.3851 0.8893
0.3523 2.0 2366 0.3124 0.9088
0.1158 3.0 3549 0.2772 0.9210

Framework versions

  • Transformers 4.19.2
  • Pytorch 1.11.0+cu113
  • Datasets 2.2.2
  • Tokenizers 0.12.1