finetuned-blurr-nonblur
This model is a fine-tuned version of google/vit-base-patch16-224-in21k on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.2435
- Accuracy: 0.9241
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: 2e-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
0.6486 | 1.0 | 14 | 0.6255 | 0.6646 |
0.552 | 2.0 | 28 | 0.5737 | 0.6772 |
0.4207 | 3.0 | 42 | 0.5175 | 0.7975 |
0.3545 | 4.0 | 56 | 0.4484 | 0.8861 |
0.2082 | 5.0 | 70 | 0.3621 | 0.8861 |
0.167 | 6.0 | 84 | 0.2930 | 0.9051 |
0.176 | 7.0 | 98 | 0.3003 | 0.8861 |
0.1275 | 8.0 | 112 | 0.2435 | 0.9241 |
0.11 | 9.0 | 126 | 0.2581 | 0.9051 |
0.1009 | 10.0 | 140 | 0.2474 | 0.9114 |
Framework versions
- Transformers 4.38.1
- Pytorch 2.1.2
- Datasets 2.1.0
- Tokenizers 0.15.2
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Model tree for Amanaccessassist/finetuned-blurr-nonblur
Base model
google/vit-base-patch16-224-in21k