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Image Classification

Classifies cat and dog images using a subset of the cats_vs_dogs dataset.
Uses PyTorch for the preprocessing, training, and inference.

  output_dir="cats_vs_dogs_model"
  remove_unused_columns=False
  evaluation_strategy="epoch"
  save_strategy="epoch"
  learning_rate=5e-5
  per_device_train_batch_size=16
  gradient_accumulation_steps=4
  per_device_eval_batch_size=16
  num_train_epochs=3
  warmup_ratio=0.1
  logging_steps=10
  load_best_model_at_end=True
  metric_for_best_model="accuracy"
  push_to_hub=True

Note: during the training, I tried adjusting some of the above hyperparameters (like making the learning rate 0.1 as we have seen in class). But then the model could only classify cats and not dogs.

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Dataset used to train ashleyradford/cats_vs_dogs_model