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resnet-50-finetuned-resnet50_0831

This model is a fine-tuned version of microsoft/resnet-50 on the imagefolder dataset. It achieves the following results on the evaluation set:

  • Loss: 0.0862
  • Accuracy: 0.9764

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: 32
  • eval_batch_size: 32
  • seed: 42
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 128
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_ratio: 0.1
  • num_epochs: 20

Training results

Training Loss Epoch Step Validation Loss Accuracy
0.9066 1.0 223 0.8770 0.6659
0.5407 2.0 446 0.4251 0.7867
0.3614 3.0 669 0.2009 0.9390
0.3016 4.0 892 0.1362 0.9582
0.2358 5.0 1115 0.1139 0.9676
0.247 6.0 1338 0.1081 0.9698
0.2135 7.0 1561 0.1027 0.9720
0.2043 8.0 1784 0.1026 0.9695
0.2165 9.0 2007 0.0957 0.9733
0.1983 10.0 2230 0.0936 0.9736
0.2116 11.0 2453 0.0949 0.9736
0.2341 12.0 2676 0.0905 0.9755
0.2004 13.0 2899 0.0901 0.9739
0.1956 14.0 3122 0.0877 0.9755
0.1668 15.0 3345 0.0847 0.9764
0.1855 16.0 3568 0.0850 0.9755
0.18 17.0 3791 0.0897 0.9745
0.1772 18.0 4014 0.0852 0.9755
0.1881 19.0 4237 0.0845 0.9764
0.2145 20.0 4460 0.0862 0.9764

Framework versions

  • Transformers 4.21.1
  • Pytorch 1.12.1
  • Datasets 2.4.0
  • Tokenizers 0.12.1
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Evaluation results