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metadata
license: apache-2.0
base_model: facebook/convnextv2-base-1k-224
tags:
  - generated_from_trainer
datasets:
  - imagefolder
metrics:
  - accuracy
model-index:
  - name: convnextv2-base-1k-224-finetuned-cassava-leaf-disease-randomflip
    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: 0.8766355140186916

convnextv2-base-1k-224-finetuned-cassava-leaf-disease-randomflip

This model is a fine-tuned version of facebook/convnextv2-base-1k-224 on the imagefolder dataset. It achieves the following results on the evaluation set:

  • Loss: 0.3704
  • Accuracy: 0.8766

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: 400
  • eval_batch_size: 400
  • seed: 42
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 1600
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_ratio: 0.1
  • num_epochs: 16

Training results

Training Loss Epoch Step Validation Loss Accuracy
1.5605 0.98 12 1.2754 0.6150
1.2015 1.96 24 0.9009 0.6290
0.9048 2.94 36 0.6987 0.7701
0.7362 4.0 49 0.5497 0.8206
0.5294 4.98 61 0.4712 0.8542
0.4777 5.96 73 0.4451 0.8547
0.458 6.94 85 0.4197 0.8579
0.4208 8.0 98 0.4084 0.8682
0.4042 8.98 110 0.3930 0.8692
0.4071 9.96 122 0.3879 0.8743
0.3868 10.94 134 0.3923 0.8715
0.3849 12.0 147 0.3763 0.8748
0.3744 12.98 159 0.3732 0.8776
0.3739 13.96 171 0.3708 0.8748
0.361 14.94 183 0.3693 0.8818
0.3725 15.67 192 0.3704 0.8766

Framework versions

  • Transformers 4.39.3
  • Pytorch 2.2.1
  • Datasets 2.18.0
  • Tokenizers 0.15.1