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metadata
license: apache-2.0
base_model: facebook/convnextv2-base-22k-384
tags:
  - generated_from_trainer
datasets:
  - imagefolder
metrics:
  - accuracy
model-index:
  - name: convnext-base-8e-5-15ep
    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: 0.9369047619047619

convnext-base-8e-5-15ep

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

  • Loss: 0.3097
  • Accuracy: 0.9369

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: 8e-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: cosine
  • num_epochs: 15

Training results

Training Loss Epoch Step Validation Loss Accuracy
0.5403 1.0 1099 0.4231 0.8744
0.4376 2.0 2198 0.3817 0.8899
0.3601 3.0 3297 0.3818 0.9018
0.3202 4.0 4396 0.3153 0.9201
0.2463 5.0 5495 0.3216 0.9229
0.2051 6.0 6594 0.3338 0.9213
0.2108 7.0 7693 0.3224 0.9272
0.1568 8.0 8792 0.3127 0.9356
0.1491 9.0 9891 0.3258 0.9352
0.0998 10.0 10990 0.3257 0.9348
0.0728 11.0 12089 0.3289 0.9368
0.0872 12.0 13188 0.3288 0.9408
0.0731 13.0 14287 0.3320 0.9408
0.0693 14.0 15386 0.3270 0.9423
0.0586 15.0 16485 0.3251 0.9427

Framework versions

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