metadata

license: apache-2.0
base_model: akahana/vit-base-cats-vs-dogs
tags:
  - generated_from_trainer
datasets:
  - cats_vs_dogs
metrics:
  - accuracy
model-index:
  - name: cat_or_dogs
    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: 0.9820589491670226

cat_or_dogs

This model is a fine-tuned version of akahana/vit-base-cats-vs-dogs on the cats_vs_dogs dataset. It achieves the following results on the evaluation set:

Loss: 0.0561
Accuracy: 0.9821

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: 1e-06
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: cosine_with_restarts
num_epochs: 3
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.0389	1.0	1171	0.0638	0.9793
0.0682	2.0	2342	0.0510	0.9812
0.0623	3.0	3513	0.0561	0.9821

Framework versions

Transformers 4.37.2
Pytorch 2.1.0+cu121
Datasets 2.17.1
Tokenizers 0.15.2