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rotated_maps

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README.md ADDED
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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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+
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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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+
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+ # vit-large-patch16-224-testing-dungeons-lora-23Nov24-008
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+
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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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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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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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+
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+ ### Training results
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+
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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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+
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+
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+ ### Framework versions
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+
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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
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+ {
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+ "alpha_pattern": {},
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+ "auto_mapping": {
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+ "base_model_class": "ViTForImageClassification",
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+ "parent_library": "transformers.models.vit.modeling_vit"
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+ },
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+ "base_model_name_or_path": "google/vit-large-patch16-224",
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+ "bias": "none",
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+ "fan_in_fan_out": false,
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+ "inference_mode": true,
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+ "init_lora_weights": true,
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+ "classifier"
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+ ],
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+ "peft_type": "LORA",
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+ "r": 16,
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+ "value",
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+ "query"
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+ ],
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+ "task_type": null,
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+ "use_dora": false,
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+ "use_rslora": false
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+ }
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+ {
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+ "do_normalize": true,
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+ "resample": 2,
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+ "height": 224,
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+ "width": 224
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+ }
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