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road_convnanov2_384_Model

Image Classification
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convnextv2
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road_convnanov2_384_Model / README.md
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metadata
license: apache-2.0
base_model: microsoft/resnet-50
tags:
  - generated_from_trainer
metrics:
  - accuracy
model-index:
  - name: freeway_resnet50_Model
    results: []

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freeway_resnet50_Model

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

  • Loss: 0.0047
  • Accuracy: 1.0

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: 64
  • eval_batch_size: 64
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 20

Training results

Training Loss Epoch Step Validation Loss Accuracy
0.3403 0.4808 100 0.3006 0.9454
0.3093 0.9615 200 0.2498 0.9540
0.2743 1.4423 300 0.2004 0.9666
0.2375 1.9231 400 0.1552 0.9798
0.2118 2.4038 500 0.1143 0.9852
0.1953 2.8846 600 0.1095 0.9844
0.1807 3.3654 700 0.0893 0.9895
0.1623 3.8462 800 0.0682 0.9914
0.1414 4.3269 900 0.0560 0.9941
0.1296 4.8077 1000 0.0511 0.9933
0.1195 5.2885 1100 0.0344 0.9957
0.1114 5.7692 1200 0.0303 0.9984
0.1034 6.25 1300 0.0298 0.9965
0.0994 6.7308 1400 0.0257 0.9987
0.0907 7.2115 1500 0.0225 0.9992
0.0881 7.6923 1600 0.0201 0.9987
0.0801 8.1731 1700 0.0157 1.0
0.0764 8.6538 1800 0.0141 0.9995
0.0746 9.1346 1900 0.0142 0.9995
0.0715 9.6154 2000 0.0115 0.9995
0.074 10.0962 2100 0.0124 0.9992
0.0677 10.5769 2200 0.0102 0.9995
0.0679 11.0577 2300 0.0101 0.9995
0.068 11.5385 2400 0.0110 0.9992
0.0589 12.0192 2500 0.0081 0.9997
0.0581 12.5 2600 0.0090 0.9995
0.058 12.9808 2700 0.0080 0.9995
0.0559 13.4615 2800 0.0082 0.9997
0.0547 13.9423 2900 0.0062 1.0
0.0493 14.4231 3000 0.0061 1.0
0.0506 14.9038 3100 0.0054 1.0
0.0466 15.3846 3200 0.0068 0.9995
0.0506 15.8654 3300 0.0055 1.0
0.0481 16.3462 3400 0.0053 1.0
0.0523 16.8269 3500 0.0053 1.0
0.0537 17.3077 3600 0.0061 0.9995
0.0474 17.7885 3700 0.0049 1.0
0.0511 18.2692 3800 0.0054 1.0
0.0474 18.75 3900 0.0052 1.0
0.0456 19.2308 4000 0.0062 0.9997
0.0385 19.7115 4100 0.0047 1.0

Framework versions

  • Transformers 4.42.0.dev0
  • Pytorch 2.1.1
  • Datasets 2.19.2
  • Tokenizers 0.19.1