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resnet-50-finetuned-dog-vs-cat

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

  • Loss: 0.0577
  • Accuracy: 0.9919

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: 3

Training results

Training Loss Epoch Step Validation Loss Accuracy
0.3357 1.0 164 0.2255 0.9868
0.1683 2.0 329 0.0577 0.9919
0.1448 2.99 492 0.0460 0.9919

Framework versions

  • Transformers 4.38.2
  • Pytorch 2.2.1+cu121
  • Datasets 2.18.0
  • Tokenizers 0.15.2
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Finetuned from

Dataset used to train cppgohan/resnet-50-finetuned-dog-vs-cat

Evaluation results