README.md

metadata

license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - fl_image_category_ds
metrics:
  - accuracy
model-index:
  - name: fl_image_category
    results:
      - task:
          name: Image Classification
          type: image-classification
        dataset:
          name: fl_image_category_ds
          type: fl_image_category_ds
          config: default
          split: train
          args: default
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.5995732574679943

fl_image_category

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

• Loss: 1.0728
• Accuracy: 0.5996

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
1.3061	1.0	88	1.2575	0.5349
1.1435	2.0	176	1.1084	0.5946
1.079	3.0	264	1.0728	0.5996

Framework versions

• Transformers 4.25.1
• Pytorch 1.13.1
• Datasets 2.8.0
• Tokenizers 0.13.2