vit-base-beans
This model is a fine-tuned version of google/vit-base-patch16-224-in21k on the beans dataset. It achieves the following results on the evaluation set:
- Loss: 0.0505
- Accuracy: 0.9850
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: 0.0002
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 8
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.1166 | 1.54 | 100 | 0.0764 | 0.9850 |
| 0.1607 | 3.08 | 200 | 0.2114 | 0.9398 |
| 0.0067 | 4.62 | 300 | 0.0692 | 0.9774 |
| 0.005 | 6.15 | 400 | 0.0944 | 0.9624 |
| 0.0043 | 7.69 | 500 | 0.0505 | 0.9850 |
Framework versions
- Transformers 4.16.2
- Pytorch 1.10.0+cu111
- Datasets 1.18.3
- Tokenizers 0.11.0
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Model tree for nickmuchi/vit-base-beans
Base model
google/vit-base-patch16-224-in21kDataset used to train nickmuchi/vit-base-beans
Evaluation results
- Accuracy on beansself-reported0.985
- Accuracy on beanstest set verified0.969
- Precision Macro on beanstest set verified0.972
- Precision Micro on beanstest set verified0.969
- Precision Weighted on beanstest set verified0.971
- Recall Macro on beanstest set verified0.969
- Recall Micro on beanstest set verified0.969
- Recall Weighted on beanstest set verified0.969
- F1 Macro on beanstest set verified0.969
- F1 Micro on beanstest set verified0.969