README.md

metadata

license: apache-2.0
tags:
  - image-classification
  - generated_from_trainer
datasets:
  - food101
metrics:
  - accuracy
model-index:
  - name: vit-base-food101-demo-v5
    results:
      - task:
          name: Image Classification
          type: image-classification
        dataset:
          name: food101
          type: food101
          args: default
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.8558811881188119
      - task:
          type: image-classification
          name: Image Classification
        dataset:
          name: food101
          type: food101
          config: default
          split: validation
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.7952079207920792
            verified: true
          - name: Precision Macro
            type: precision
            value: 0.8087208389002668
            verified: true
          - name: Precision Micro
            type: precision
            value: 0.7952079207920792
            verified: true
          - name: Precision Weighted
            type: precision
            value: 0.8087208389002665
            verified: true
          - name: Recall Macro
            type: recall
            value: 0.7952079207920792
            verified: true
          - name: Recall Micro
            type: recall
            value: 0.7952079207920792
            verified: true
          - name: Recall Weighted
            type: recall
            value: 0.7952079207920792
            verified: true
          - name: F1 Macro
            type: f1
            value: 0.7971943899991044
            verified: true
          - name: F1 Micro
            type: f1
            value: 0.7952079207920791
            verified: true
          - name: F1 Weighted
            type: f1
            value: 0.7971943899991044
            verified: true
          - name: loss
            type: loss
            value: 0.7573962807655334
            verified: true

vit-base-food101-demo-v5

This model is a fine-tuned version of google/vit-base-patch16-224-in21k on the food101 dataset. It achieves the following results on the evaluation set:

• Loss: 0.5434
• Accuracy: 0.8559

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: 0.0002
• 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: 4
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
1.6283	1.0	4735	0.9875	0.7409
0.9874	2.0	9470	0.7967	0.7894
0.7102	3.0	14205	0.6455	0.8255
0.4917	4.0	18940	0.5502	0.8524

Framework versions

• Transformers 4.19.2
• Pytorch 1.11.0+cu113
• Datasets 2.2.1
• Tokenizers 0.12.1