Drugs_detection
This model is a fine-tuned version of google/vit-base-patch16-224-in21k on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 0.0447
- Accuracy: 0.9854
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: 5e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 5
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
0.0746 | 0.9670 | 22 | 0.0708 | 0.9757 |
0.0263 | 1.9780 | 45 | 0.0522 | 0.9854 |
0.0179 | 2.9890 | 68 | 0.0829 | 0.9612 |
0.0181 | 4.0 | 91 | 0.0438 | 0.9903 |
0.0255 | 4.8352 | 110 | 0.0447 | 0.9854 |
Framework versions
- Transformers 4.40.1
- Pytorch 2.2.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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Base model
google/vit-base-patch16-224-in21k