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vit-large-patch16-224-testing-dungeons-lora-23Nov24-008
This model is a fine-tuned version of google/vit-large-patch16-224 on the rotated_maps dataset. It achieves the following results on the evaluation set:
- Loss: 0.2048
- Accuracy: 0.9630
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: 0.005
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 10
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
No log | 0.6667 | 1 | 1.5395 | 0.1852 |
No log | 2.0 | 3 | 1.2052 | 0.4815 |
No log | 2.6667 | 4 | 1.1291 | 0.5185 |
No log | 4.0 | 6 | 0.4352 | 0.8148 |
No log | 4.6667 | 7 | 0.3886 | 0.9259 |
No log | 6.0 | 9 | 0.2470 | 0.9630 |
0.9407 | 6.6667 | 10 | 0.2048 | 0.9630 |
Framework versions
- PEFT 0.13.2
- Transformers 4.46.2
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3
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Model tree for griffio/vit-large-patch16-224-testing-dungeons-lora-23Nov24-008
Base model
google/vit-large-patch16-224Evaluation results
- Accuracy on rotated_mapsvalidation set self-reported0.963