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vit-large-augmented-ph2-patch-16
This model is a fine-tuned version of google/vit-large-patch16-224-in21k on the ahishamm/Augmented_PH2_db_sharpened dataset. It achieves the following results on the evaluation set:
- Loss: 0.5307
- Accuracy: 0.8735
- Recall: 0.8735
- F1: 0.8735
- Precision: 0.8735
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: 4
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Recall | F1 | Precision |
|---|---|---|---|---|---|---|---|
| 0.2064 | 0.36 | 50 | 0.5307 | 0.8735 | 0.8735 | 0.8735 | 0.8735 |
| 0.1145 | 0.72 | 100 | 0.8837 | 0.7470 | 0.7470 | 0.7470 | 0.7470 |
| 0.4187 | 1.09 | 150 | 0.9485 | 0.6256 | 0.6256 | 0.6256 | 0.6256 |
| 0.0756 | 1.45 | 200 | 0.6959 | 0.8325 | 0.8325 | 0.8325 | 0.8325 |
| 0.0696 | 1.81 | 250 | 0.7697 | 0.8171 | 0.8171 | 0.8171 | 0.8171 |
| 0.0251 | 2.17 | 300 | 0.7361 | 0.8325 | 0.8325 | 0.8325 | 0.8325 |
| 0.0604 | 2.54 | 350 | 0.9345 | 0.8427 | 0.8427 | 0.8427 | 0.8427 |
| 0.0005 | 2.9 | 400 | 0.9581 | 0.8513 | 0.8513 | 0.8513 | 0.8513 |
| 0.0005 | 3.26 | 450 | 1.0674 | 0.8444 | 0.8444 | 0.8444 | 0.8444 |
| 0.005 | 3.62 | 500 | 0.9464 | 0.8564 | 0.8564 | 0.8564 | 0.8564 |
| 0.0002 | 3.99 | 550 | 0.9575 | 0.8564 | 0.8564 | 0.8564 | 0.8564 |
Framework versions
- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3
