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Rice-Plant-20-Epochs-Model

Image Classification
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Safetensors
vit
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Rice-Plant-20-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:
  - imagefolder
metrics:
  - accuracy
  - f1
model-index:
  - name: Rice-Plant-20-Epochs-Model
    results:
      - task:
          name: Image Classification
          type: image-classification
        dataset:
          name: imagefolder
          type: imagefolder
          config: default
          split: train
          args: default
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.9719626168224299
          - name: F1
            type: f1
            value: 0.9719154614454629

Rice-Plant-20-Epochs-Model

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

  • Loss: 0.1306
  • Accuracy: 0.9720
  • F1: 0.9719

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: 20

Training results

Training Loss Epoch Step Validation Loss Accuracy F1
1.0906 1.0 116 0.6826 0.8660 0.8676
0.3792 2.0 232 0.3327 0.9470 0.9474
0.1934 3.0 348 0.2876 0.9283 0.9285
0.1157 4.0 464 0.2187 0.9470 0.9470
0.0849 5.0 580 0.1614 0.9688 0.9689
0.0675 6.0 696 0.1326 0.9688 0.9688
0.0561 7.0 812 0.1227 0.9688 0.9688
0.0485 8.0 928 0.1306 0.9720 0.9719
0.0416 9.0 1044 0.1356 0.9720 0.9719
0.0369 10.0 1160 0.1184 0.9688 0.9688
0.0335 11.0 1276 0.1281 0.9720 0.9720
0.0308 12.0 1392 0.1129 0.9720 0.9719
0.0285 13.0 1508 0.1074 0.9720 0.9719
0.0267 14.0 1624 0.1061 0.9720 0.9719
0.0253 15.0 1740 0.1049 0.9720 0.9719
0.0241 16.0 1856 0.1048 0.9720 0.9719
0.0232 17.0 1972 0.1045 0.9720 0.9719
0.0225 18.0 2088 0.1036 0.9720 0.9719
0.0221 19.0 2204 0.1035 0.9720 0.9719
0.0219 20.0 2320 0.1036 0.9720 0.9719

Framework versions

  • Transformers 4.35.0
  • Pytorch 2.1.0+cu118
  • Datasets 2.14.6
  • Tokenizers 0.14.1