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--- |
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license: apache-2.0 |
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base_model: facebook/dinov2-base |
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tags: |
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- generated_from_trainer |
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metrics: |
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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: outputs |
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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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# outputs |
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This model is a fine-tuned version of [facebook/dinov2-base](https://huggingface.co/facebook/dinov2-base) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0742 |
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- Precision: 0.9306 |
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- Recall: 0.8969 |
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- F1: 0.9135 |
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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: 1e-06 |
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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: 8 |
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- total_train_batch_size: 128 |
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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: 15 |
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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 | Precision | Recall | F1 | |
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|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:| |
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| 0.5948 | 0.98 | 39 | 0.4487 | 0.1103 | 0.0658 | 0.0824 | |
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| 0.2211 | 1.98 | 79 | 0.2079 | 0.8179 | 0.5614 | 0.6658 | |
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| 0.1241 | 2.98 | 119 | 0.1378 | 0.8880 | 0.7390 | 0.8067 | |
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| 0.0954 | 3.99 | 159 | 0.1117 | 0.8916 | 0.8114 | 0.8496 | |
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| 0.0801 | 4.99 | 199 | 0.0980 | 0.9167 | 0.8322 | 0.8724 | |
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| 0.0716 | 5.99 | 239 | 0.0875 | 0.9245 | 0.8596 | 0.8909 | |
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| 0.0641 | 7.0 | 279 | 0.0871 | 0.9231 | 0.8421 | 0.8807 | |
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| 0.0615 | 8.0 | 319 | 0.0804 | 0.9318 | 0.8838 | 0.9071 | |
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| 0.056 | 8.98 | 358 | 0.0793 | 0.9257 | 0.8882 | 0.9065 | |
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| 0.0541 | 9.98 | 398 | 0.0761 | 0.9335 | 0.8925 | 0.9126 | |
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| 0.0532 | 10.98 | 438 | 0.0767 | 0.9339 | 0.8827 | 0.9076 | |
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| 0.053 | 11.99 | 478 | 0.0758 | 0.9312 | 0.8904 | 0.9103 | |
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| 0.048 | 12.99 | 518 | 0.0743 | 0.9324 | 0.8925 | 0.9120 | |
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| 0.047 | 13.99 | 558 | 0.0750 | 0.9303 | 0.8925 | 0.9110 | |
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| 0.0476 | 14.67 | 585 | 0.0742 | 0.9306 | 0.8969 | 0.9135 | |
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### Framework versions |
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- Transformers 4.37.0 |
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- Pytorch 1.13.1+cu117 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
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