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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-in21k |
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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-in21k-testing-dungeons-lora-27Dec24-0001 |
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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: 0.9607142857142857 |
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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-in21k-testing-dungeons-lora-27Dec24-0001 |
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This model is a fine-tuned version of [google/vit-large-patch16-224-in21k](https://huggingface.co/google/vit-large-patch16-224-in21k) on the rotated_maps dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1076 |
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- Accuracy: 0.9607 |
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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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- lr_scheduler_warmup_ratio: 0.1 |
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- num_epochs: 12 |
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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 | 0.7273 | 2 | 1.5502 | 0.2946 | |
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| No log | 1.7273 | 4 | 1.1408 | 0.6696 | |
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| No log | 2.7273 | 6 | 1.0113 | 0.6036 | |
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| No log | 3.7273 | 8 | 0.6030 | 0.8411 | |
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| 5.1081 | 4.7273 | 10 | 0.4665 | 0.8625 | |
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| 5.1081 | 5.7273 | 12 | 0.4145 | 0.8643 | |
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| 5.1081 | 6.7273 | 14 | 0.2846 | 0.9107 | |
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| 5.1081 | 7.7273 | 16 | 0.2386 | 0.9125 | |
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| 5.1081 | 8.7273 | 18 | 0.1564 | 0.9554 | |
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| 0.7653 | 9.7273 | 20 | 0.1178 | 0.9679 | |
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| 0.7653 | 10.7273 | 22 | 0.1241 | 0.9536 | |
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| 0.7653 | 11.7273 | 24 | 0.1076 | 0.9607 | |
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### Framework versions |
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- PEFT 0.14.0 |
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- Transformers 4.47.1 |
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- Pytorch 2.5.1+cu121 |
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- Datasets 3.2.0 |
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- Tokenizers 0.21.0 |
