README.md

metadata

license: apache-2.0
base_model: google/vit-base-patch16-224
tags:
  - image-classification
  - generated_from_trainer
datasets:
  - imagefolder
metrics:
  - accuracy
  - f1
model-index:
  - name: fine-tuned-augmented
    results:
      - task:
          name: Image Classification
          type: image-classification
        dataset:
          name: custom_dataset_augmented
          type: imagefolder
          config: default
          split: validation
          args: default
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.23333333333333334
          - name: F1
            type: f1
            value: 0.04545454545454546

fine-tuned-augmented

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

• Loss: 2.2134
• Accuracy: 0.2333
• F1: 0.0455

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: 8
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 10

Training results

Framework versions

• Transformers 4.34.0
• Pytorch 2.0.1+cu118
• Datasets 2.14.5
• Tokenizers 0.14.1