README.md

metadata

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