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priyankloco/resnet-101-finetuned_resnet101-sgd-optimizer20-autotags

sourceHugging Faceapache-2.0updated 3y agoView on Hugging Face
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Model Card

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resnet-101-finetuned_resnet101-sgd-optimizer20-autotags

This model is a fine-tuned version of microsoft/resnet-101 on the imagefolder dataset. It achieves the following results on the evaluation set:

  • —Loss: 0.3318
  • —Accuracy: 0.8848

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: 0.1
  • —trainbatchsize: 16
  • —evalbatchsize: 16
  • —seed: 42
  • —gradientaccumulationsteps: 4
  • —totaltrainbatch_size: 64
  • —optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • —lrschedulertype: linear
  • —lrschedulerwarmup_ratio: 0.1
  • —num_epochs: 20

Training results

Training LossEpochStepValidation LossAccuracy
1.13020.99651.00400.6724
1.17081.991301.48560.5495
1.1412.991951.14860.6352
1.01193.992600.88290.7314
0.80914.993250.83010.7419
0.78785.993900.81210.7333
0.68276.994550.60470.7990
0.55257.995200.60280.8048
0.57878.995850.51830.8352
0.47979.996500.47370.8543
0.422410.997150.49430.8305
0.438911.997800.41620.8629
0.414212.998450.40000.8629
0.314413.999100.38330.8695
0.291514.999750.36880.8733
0.330215.9910400.36430.8810
0.295416.9911050.34460.8867
0.218617.9911700.35710.8905
0.181218.9912350.33340.8886
0.191119.9913000.33180.8848

Framework versions

  • —Transformers 4.25.1
  • —Pytorch 1.13.1+cu117
  • —Datasets 2.11.0
  • —Tokenizers 0.13.2