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--- |
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library_name: peft |
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license: apache-2.0 |
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base_model: google/vit-large-patch16-224 |
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tags: |
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- image-classification |
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- generated_from_trainer |
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datasets: |
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- imagefolder |
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metrics: |
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- accuracy |
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model-index: |
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- name: vit-large-patch16-224-testing-dungeons-lora-23Nov24-008 |
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results: |
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- task: |
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type: image-classification |
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name: Image Classification |
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dataset: |
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name: rotated_maps |
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type: imagefolder |
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config: default |
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split: validation |
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args: default |
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metrics: |
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- type: accuracy |
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value: 0.9629629629629629 |
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name: Accuracy |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# vit-large-patch16-224-testing-dungeons-lora-23Nov24-008 |
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This model is a fine-tuned version of [google/vit-large-patch16-224](https://huggingface.co/google/vit-large-patch16-224) on the rotated_maps dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2048 |
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- Accuracy: 0.9630 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 0.005 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 32 |
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- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: linear |
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- num_epochs: 10 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:------:|:----:|:---------------:|:--------:| |
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| No log | 0.6667 | 1 | 1.5395 | 0.1852 | |
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| No log | 2.0 | 3 | 1.2052 | 0.4815 | |
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| No log | 2.6667 | 4 | 1.1291 | 0.5185 | |
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| No log | 4.0 | 6 | 0.4352 | 0.8148 | |
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| No log | 4.6667 | 7 | 0.3886 | 0.9259 | |
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| No log | 6.0 | 9 | 0.2470 | 0.9630 | |
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| 0.9407 | 6.6667 | 10 | 0.2048 | 0.9630 | |
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### Framework versions |
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- PEFT 0.13.2 |
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- Transformers 4.46.2 |
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- Pytorch 2.5.1+cu121 |
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- Datasets 3.1.0 |
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- Tokenizers 0.20.3 |
