Thamer / resnet-fine_tuned

huggingface.co
Total runs: 6
24-hour runs: 0
7-day runs: 0
30-day runs: 1
Model's Last Updated: September 09 2023
image-classification

Introduction of resnet-fine_tuned

Model Details of resnet-fine_tuned

resnet-fine_tuned

This model is a fine-tuned version of microsoft/resnet-34 on the Falah/Alzheimer_MRI dataset. It achieves the following results on the evaluation set:

  • Loss: 0.1983
  • Accuracy: 0.9219
Training hyperparameters

The following hyperparameters were used during training:

  • learning_rate: 0.0002
  • train_batch_size: 16
  • eval_batch_size: 16
  • seed: 42
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 64
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_ratio: 0.1
  • num_epochs: 15
Training results
Training Loss Epoch Step Validation Loss Accuracy
0.9041 1.0 80 0.9659 0.5352
0.8743 2.0 160 0.9348 0.5797
0.7723 3.0 240 0.7793 0.6594
0.6864 4.0 320 0.6799 0.7031
0.5347 5.0 400 0.5596 0.7703
0.4282 6.0 480 0.5078 0.7766
0.4315 7.0 560 0.5455 0.7680
0.3747 8.0 640 0.4203 0.8266
0.2977 9.0 720 0.3926 0.8469
0.2252 10.0 800 0.3024 0.8742
0.2675 11.0 880 0.2731 0.8906
0.2136 12.0 960 0.3045 0.875
0.1998 13.0 1040 0.2370 0.9
0.2406 14.0 1120 0.2387 0.9086
0.1873 15.0 1200 0.1983 0.9219
Framework versions
  • Transformers 4.31.0
  • Pytorch 2.0.1+cpu
  • Datasets 2.13.1
  • Tokenizers 0.13.3

Runs of Thamer resnet-fine_tuned on huggingface.co

6
Total runs
0
24-hour runs
0
3-day runs
0
7-day runs
1
30-day runs

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