vit-base-trashnet-demo
This model is a fine-tuned version of google/vit-base-patch16-224-in21k on the edwinpalegre/trashnet-enhanced dataset. It achieves the following results on the evaluation set:
- Loss: 0.0701
- Accuracy: 0.9822
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: 64
- eval_batch_size: 8
- seed: 42
- 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 |
---|---|---|---|---|
0.2636 | 0.4 | 100 | 0.2388 | 0.9394 |
0.1748 | 0.8 | 200 | 0.1414 | 0.9623 |
0.1231 | 1.2 | 300 | 0.1565 | 0.9545 |
0.0769 | 1.61 | 400 | 0.1074 | 0.9713 |
0.0556 | 2.01 | 500 | 0.0994 | 0.9726 |
0.0295 | 2.41 | 600 | 0.0720 | 0.9812 |
0.0311 | 2.81 | 700 | 0.0774 | 0.9806 |
0.0061 | 3.21 | 800 | 0.0703 | 0.9822 |
0.0289 | 3.61 | 900 | 0.0701 | 0.9822 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0
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