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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
planes
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
