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metadata
license: apache-2.0
tags:
  - generated_from_trainer
metrics:
  - precision
  - recall
  - f1
  - accuracy
model-index:
  - name: convnext-tiny-224_finetuned
    results: []

convnext-tiny-224_finetuned

This model is a fine-tuned version of facebook/convnext-tiny-224 on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.0895
  • Precision: 0.9807
  • Recall: 0.9608
  • F1: 0.9702
  • Accuracy: 0.9776

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: 16
  • eval_batch_size: 16
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 10
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Precision Recall F1 Accuracy
No log 1.0 46 0.3080 0.9096 0.6852 0.7206 0.8365
No log 2.0 92 0.1644 0.9660 0.9176 0.9386 0.9551
No log 3.0 138 0.0974 0.9742 0.9586 0.9661 0.9744
No log 4.0 184 0.0795 0.9829 0.9670 0.9746 0.9808
No log 5.0 230 0.0838 0.9807 0.9608 0.9702 0.9776
No log 6.0 276 0.0838 0.9807 0.9608 0.9702 0.9776
No log 7.0 322 0.0803 0.9829 0.9670 0.9746 0.9808
No log 8.0 368 0.0869 0.9807 0.9608 0.9702 0.9776
No log 9.0 414 0.0897 0.9807 0.9608 0.9702 0.9776
No log 10.0 460 0.0895 0.9807 0.9608 0.9702 0.9776

Framework versions

  • Transformers 4.22.1
  • Pytorch 1.12.1+cu113
  • Datasets 2.5.1
  • Tokenizers 0.12.1