planes-trains-automobiles

This model is a fine-tuned version of google/vit-base-patch16-224-in21k on the huggingpics dataset. It achieves the following results on the evaluation set:

  • Loss: 0.0534
  • Accuracy: 0.9851

Model description

Autogenerated by HuggingPics🤗🖼️

Create your own image classifier for anything by running the demo on Google Colab.

Report any issues with the demo at the github repo.

Example Images

automobiles

automobiles

planes

planes

trains

trains

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: 2e-05
  • train_batch_size: 8
  • eval_batch_size: 8
  • seed: 1337
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 4
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Accuracy
0.0283 1.0 48 0.0434 0.9851
0.0224 2.0 96 0.0548 0.9851
0.0203 3.0 144 0.0445 0.9851
0.0195 4.0 192 0.0534 0.9851

Framework versions

  • Transformers 4.9.2
  • Pytorch 1.9.0+cu102
  • Datasets 1.11.0
  • Tokenizers 0.10.3
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