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--- |
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library_name: transformers |
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license: apache-2.0 |
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base_model: google/vit-base-patch16-224 |
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tags: |
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- generated_from_trainer |
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metrics: |
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- accuracy |
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- precision |
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- recall |
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- f1 |
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model-index: |
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- name: wmc-wmk811-v0-vit-special_map_det_0917 |
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results: [] |
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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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# wmc-wmk811-v0-vit-special_map_det_0917 |
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This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co./google/vit-base-patch16-224) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0354 |
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- Accuracy: 0.9882 |
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- Precision: 0.9872 |
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- Recall: 0.9854 |
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- F1: 0.9863 |
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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: 2e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 16 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 64 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_ratio: 0.1 |
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- num_epochs: 1 |
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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 | Precision | Recall | F1 | |
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|:-------------:|:------:|:----:|:---------------:|:--------:|:---------:|:------:|:------:| |
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| 0.0471 | 0.2158 | 400 | 0.0651 | 0.9766 | 0.9793 | 0.9662 | 0.9724 | |
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| 0.0664 | 0.4317 | 800 | 0.0445 | 0.9874 | 0.9879 | 0.9828 | 0.9853 | |
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| 0.0391 | 0.6475 | 1200 | 0.0476 | 0.9833 | 0.9826 | 0.9785 | 0.9805 | |
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| 0.0478 | 0.8633 | 1600 | 0.0354 | 0.9882 | 0.9872 | 0.9854 | 0.9863 | |
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### Framework versions |
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- Transformers 4.44.2 |
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- Pytorch 2.4.0+cu121 |
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- Datasets 3.0.0 |
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- Tokenizers 0.19.1 |
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