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metadata
license: apache-2.0
base_model: facebook/convnextv2-tiny-22k-384
tags:
  - generated_from_trainer
datasets:
  - imagefolder
metrics:
  - accuracy
model-index:
  - name: cconvnext-tiny-15ep-1e-4
    results:
      - task:
          name: Image Classification
          type: image-classification
        dataset:
          name: imagefolder
          type: imagefolder
          config: default
          split: validation
          args: default
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.9375

cconvnext-tiny-15ep-1e-4

This model is a fine-tuned version of facebook/convnextv2-tiny-22k-384 on the imagefolder dataset. It achieves the following results on the evaluation set:

  • Loss: 0.2767
  • Accuracy: 0.9375

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: 0.0001
  • train_batch_size: 32
  • eval_batch_size: 32
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: cosine
  • num_epochs: 15

Training results

Training Loss Epoch Step Validation Loss Accuracy
0.5838 1.0 550 0.4097 0.8811
0.4565 2.0 1100 0.4269 0.8763
0.3628 3.0 1650 0.3464 0.9002
0.2915 4.0 2200 0.3366 0.9066
0.2655 5.0 2750 0.3387 0.9054
0.2395 6.0 3300 0.3313 0.9125
0.2065 7.0 3850 0.3120 0.9181
0.1503 8.0 4400 0.3065 0.9221
0.1503 9.0 4950 0.2948 0.9276
0.1125 10.0 5500 0.2918 0.9304
0.1057 11.0 6050 0.2954 0.9328
0.0937 12.0 6600 0.2959 0.9336
0.0966 13.0 7150 0.2940 0.9352
0.0735 14.0 7700 0.2916 0.9340
0.0881 15.0 8250 0.2902 0.9356

Framework versions

  • Transformers 4.39.3
  • Pytorch 2.1.2
  • Datasets 2.18.0
  • Tokenizers 0.15.2