README.md

metadata

license: apache-2.0
tags:
  - image-classification
  - other-image-classification
  - generated_from_trainer
datasets:
  - AI-Lab-Makerere/beans
metrics:
  - accuracy
model-index:
  - name: vit-base-beans-demo
    results:
      - task:
          type: image-classification
          name: Image Classification
        dataset:
          name: beans
          type: beans
          args: default
        metrics:
          - type: accuracy
            value: 0.9774436090225563
            name: Accuracy

vit-base-beans-demo

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

• Loss: 0.0853
• Accuracy: 0.9774

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: 5
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.0545	1.54	100	0.1436	0.9624
0.006	3.08	200	0.1058	0.9699
0.0038	4.62	300	0.0853	0.9774

Framework versions

• Transformers 4.9.2
• Pytorch 1.9.0+cu102
• Datasets 1.11.0
• Tokenizers 0.10.3