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metadata
library_name: transformers
license: apache-2.0
base_model: facebook/convnext-large-224
tags:
  - generated_from_trainer
datasets:
  - imagefolder
metrics:
  - accuracy
model-index:
  - name: weeds24_convnext_balanced
    results:
      - task:
          name: Image Classification
          type: image-classification
        dataset:
          name: imagefolder
          type: imagefolder
          config: default
          split: test
          args: default
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.94

weeds24_convnext_balanced

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

  • Loss: 0.1908
  • Accuracy: 0.94

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: 8
  • eval_batch_size: 8
  • seed: 42
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 32
  • optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_ratio: 0.1
  • num_epochs: 10

Training results

Training Loss Epoch Step Validation Loss Accuracy
9.0308 1.0 75 2.0854 0.5067
4.0591 2.0 150 0.9363 0.8433
1.9789 3.0 225 0.5118 0.8867
1.3397 4.0 300 0.3700 0.9067
0.9292 5.0 375 0.2859 0.92
0.7772 6.0 450 0.2314 0.9233
0.8323 7.0 525 0.2472 0.9233
0.7398 8.0 600 0.2647 0.9233
0.6066 9.0 675 0.2107 0.9433
0.546 10.0 750 0.1908 0.94

Framework versions

  • Transformers 4.46.1
  • Pytorch 2.5.0+cu124
  • Datasets 3.0.2
  • Tokenizers 0.20.1