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plant-vit-model-2
This model is a fine-tuned version of google/vit-base-patch16-224-in21k on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0402
- Precision: 1.0
- Recall: 1.0
- F1: 1.0
- Accuracy: 1.0
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: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.2898 | 1.0 | 83 | 0.2431 | 0.9973 | 0.9973 | 0.9973 | 0.9973 |
| 0.2255 | 2.0 | 166 | 0.1596 | 0.9963 | 0.9963 | 0.9963 | 0.9963 |
| 0.1622 | 3.0 | 249 | 0.1105 | 0.9973 | 0.9973 | 0.9973 | 0.9973 |
| 0.1261 | 4.0 | 332 | 0.0887 | 0.9963 | 0.9963 | 0.9963 | 0.9963 |
| 0.1009 | 5.0 | 415 | 0.0645 | 0.9989 | 0.9989 | 0.9989 | 0.9989 |
| 0.0884 | 6.0 | 498 | 0.0554 | 1.0 | 1.0 | 1.0 | 1.0 |
| 0.0776 | 7.0 | 581 | 0.0489 | 0.9995 | 0.9995 | 0.9995 | 0.9995 |
| 0.0682 | 8.0 | 664 | 0.0447 | 0.9995 | 0.9995 | 0.9995 | 0.9995 |
| 0.0664 | 9.0 | 747 | 0.0411 | 1.0 | 1.0 | 1.0 | 1.0 |
| 0.0532 | 10.0 | 830 | 0.0402 | 1.0 | 1.0 | 1.0 | 1.0 |
Framework versions
- Transformers 4.28.0
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3
