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All-Plants-18-Epochs-Model

Image Classification
Transformers
Safetensors
vit
generated_from_trainer
Eval Results
Inference Endpoints
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All-Plants-18-Epochs-Model / README.md
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metadata
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
  - generated_from_trainer
datasets:
  - image_folder
metrics:
  - accuracy
  - f1
model-index:
  - name: All-Plants-18-Epochs-Model
    results:
      - task:
          name: Image Classification
          type: image-classification
        dataset:
          name: image_folder
          type: image_folder
          config: Dataset
          split: train
          args: Dataset
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.9847645429362881
          - name: F1
            type: f1
            value: 0.984922643975302

All-Plants-18-Epochs-Model

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

  • Loss: 0.0888
  • Accuracy: 0.9848
  • F1: 0.9849

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: 2e-05
  • train_batch_size: 16
  • eval_batch_size: 16
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 18

Training results

Training Loss Epoch Step Validation Loss Accuracy F1
0.9212 1.0 407 0.3931 0.9501 0.9579
0.2659 2.0 814 0.2176 0.9668 0.9674
0.137 3.0 1221 0.1481 0.9723 0.9731
0.0865 4.0 1628 0.1043 0.9834 0.9836
0.0557 5.0 2035 0.0888 0.9848 0.9849
0.0408 6.0 2442 0.0839 0.9848 0.9848
0.0289 7.0 2849 0.0920 0.9848 0.9849
0.0229 8.0 3256 0.0817 0.9834 0.9837
0.0175 9.0 3663 0.0890 0.9820 0.9823
0.0156 10.0 4070 0.0966 0.9820 0.9823
0.0121 11.0 4477 0.0809 0.9834 0.9837
0.0102 12.0 4884 0.0875 0.9820 0.9823
0.0086 13.0 5291 0.0873 0.9820 0.9823
0.0077 14.0 5698 0.0860 0.9820 0.9823
0.0068 15.0 6105 0.0876 0.9820 0.9823
0.0062 16.0 6512 0.0896 0.9820 0.9823
0.0059 17.0 6919 0.0890 0.9820 0.9823
0.0056 18.0 7326 0.0894 0.9820 0.9823

Framework versions

  • Transformers 4.35.0
  • Pytorch 2.0.0
  • Datasets 2.1.0
  • Tokenizers 0.14.1