README.md

metadata

license: apache-2.0
base_model: microsoft/resnet-50
tags:
  - generated_from_trainer
datasets:
  - cats_vs_dogs
metrics:
  - accuracy
model-index:
  - name: cat-vs-dog
    results:
      - task:
          name: Image Classification
          type: image-classification
        dataset:
          name: cats_vs_dogs
          type: cats_vs_dogs
          config: default
          split: train
          args: default
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.9653994019649722

cat-vs-dog

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: 0.1015
• Accuracy: 0.9654

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: 16
• eval_batch_size: 16
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 1

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.1574	1.0	1171	0.1065	0.9624

Framework versions

• Transformers 4.37.2
• Pytorch 2.1.0+cu121
• Datasets 2.17.1
• Tokenizers 0.15.2