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resnet-Alzheimer

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metadata
license: apache-2.0
base_model: microsoft/resnet-50
tags:
  - generated_from_trainer
metrics:
  - accuracy
model-index:
  - name: resnet-Alzheimer
    results: []
datasets:
  - Falah/Alzheimer_MRI

resnet-Alzheimer

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

  • Loss: 0.0932
  • Accuracy: 0.9795

Training hyperparameters

The following hyperparameters were used during training:

  • learning_rate: 0.002
  • 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: 50

Training results

Training Loss Epoch Step Validation Loss Accuracy
1.0127 1.0 80 0.9888 0.5088
0.9345 2.0 160 0.9422 0.5303
0.8889 3.0 240 0.8724 0.5781
0.8843 4.0 320 0.8536 0.5889
0.8397 5.0 400 0.8354 0.6152
0.8624 6.0 480 0.9221 0.5381
0.7543 7.0 560 0.7568 0.6475
0.6993 8.0 640 0.8830 0.6133
0.7045 9.0 720 0.7373 0.6582
0.6557 10.0 800 0.6076 0.7451
0.5876 11.0 880 0.7281 0.6992
0.5732 12.0 960 0.5769 0.7510
0.4864 13.0 1040 0.4457 0.8311
0.5175 14.0 1120 0.5278 0.7842
0.4865 15.0 1200 0.4164 0.8379
0.4049 16.0 1280 0.4204 0.8301
0.4167 17.0 1360 0.4720 0.8281
0.36 18.0 1440 0.4660 0.8164
0.3195 19.0 1520 0.3064 0.8770
0.3652 20.0 1600 0.2571 0.9121
0.2794 21.0 1680 0.2450 0.9150
0.2704 22.0 1760 0.2391 0.9033
0.2612 23.0 1840 0.2352 0.9277
0.2425 24.0 1920 0.4720 0.8281
0.2567 25.0 2000 0.2296 0.9131
0.2302 26.0 2080 0.3067 0.8945
0.2358 27.0 2160 0.1776 0.9375
0.2173 28.0 2240 0.1596 0.9492
0.1798 29.0 2320 0.1548 0.9414
0.197 30.0 2400 0.1740 0.9570
0.1654 31.0 2480 0.1217 0.9668
0.1896 32.0 2560 0.2552 0.9258
0.1705 33.0 2640 0.1031 0.9727
0.1689 34.0 2720 0.1011 0.9688
0.1439 35.0 2800 0.1175 0.9648
0.1606 36.0 2880 0.1805 0.9443
0.1281 37.0 2960 0.1254 0.9678
0.1518 38.0 3040 0.1184 0.9648
0.1531 39.0 3120 0.0992 0.9736
0.132 40.0 3200 0.0920 0.9775
0.134 41.0 3280 0.1391 0.9639
0.1413 42.0 3360 0.1122 0.9717
0.1097 43.0 3440 0.1171 0.9678
0.1167 44.0 3520 0.1054 0.9766
0.1388 45.0 3600 0.0932 0.9795
0.1221 46.0 3680 0.0946 0.9766
0.1099 47.0 3760 0.1116 0.9756
0.1041 48.0 3840 0.1126 0.9746
0.1025 49.0 3920 0.1114 0.9756
0.0887 50.0 4000 0.1056 0.9756

Framework versions

  • Transformers 4.38.2
  • Pytorch 2.1.0+cu121
  • Datasets 2.18.0
  • Tokenizers 0.15.2