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metadata
license: apache-2.0
tags:
  - generated_from_trainer
metrics:
  - accuracy
model-index:
  - name: resnet-18-finetuned-eurosat
    results: []

resnet-18-finetuned-eurosat

This model is a fine-tuned version of microsoft/resnet-18 on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.5506
  • Accuracy: 0.8364

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
0.3846 0.99 20 0.6352 0.7576
0.5009 1.98 40 0.6439 0.7485
0.5625 2.96 60 0.5722 0.7909
0.4928 4.0 81 0.5514 0.7970
0.4621 4.99 101 0.6104 0.7697
0.4367 5.98 121 0.5734 0.7939
0.4238 6.96 141 0.5558 0.8
0.4011 8.0 162 0.5549 0.8030
0.4129 8.99 182 0.5554 0.8061
0.384 9.98 202 0.5551 0.8152
0.3839 10.96 222 0.5742 0.8091
0.3496 12.0 243 0.5518 0.8303
0.3482 12.99 263 0.5390 0.8303
0.357 13.98 283 0.5544 0.8182
0.3341 14.96 303 0.5506 0.8364
0.3605 16.0 324 0.5546 0.8212
0.3041 16.99 344 0.5597 0.8212
0.3364 17.98 364 0.5730 0.8091
0.2976 18.96 384 0.5742 0.8091
0.3229 19.75 400 0.5653 0.8121

Framework versions

  • Transformers 4.30.1
  • Pytorch 2.0.1+cu118
  • Datasets 2.12.0
  • Tokenizers 0.13.3