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End of training
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metadata
license: apache-2.0
base_model: facebook/convnextv2-tiny-1k-224
tags:
  - generated_from_trainer
datasets:
  - imagefolder
metrics:
  - accuracy
  - precision
model-index:
  - name: convnextv2-tiny-1k-224-finetuned-bottomwear-v2
    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: 0.8981481481481481
          - name: Precision
            type: precision
            value: 0.9001054377012231

convnextv2-tiny-1k-224-finetuned-bottomwear-v2

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

  • Loss: 0.3267
  • Accuracy: 0.8981
  • Precision: 0.9001

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: 10
  • eval_batch_size: 4
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 100

Training results

Training Loss Epoch Step Validation Loss Accuracy Precision
No log 1.0 87 1.3349 0.6852 0.7395
No log 2.0 174 0.7869 0.8426 0.8543
No log 3.0 261 0.6571 0.8472 0.8712
No log 4.0 348 0.4293 0.9028 0.9122
No log 5.0 435 0.4030 0.8935 0.8953
0.916 6.0 522 0.4251 0.8657 0.8787
0.916 7.0 609 0.3536 0.8889 0.8936
0.916 8.0 696 0.3611 0.8796 0.8833
0.916 9.0 783 0.3267 0.8981 0.9001
0.916 10.0 870 0.3526 0.8796 0.8972
0.916 11.0 957 0.3694 0.8981 0.9100
0.3192 12.0 1044 0.3694 0.8935 0.9007

Framework versions

  • Transformers 4.44.0
  • Pytorch 2.4.0
  • Datasets 2.21.0
  • Tokenizers 0.19.1