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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: facebook/dinov2-small |
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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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- f1 |
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- recall |
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- precision |
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model-index: |
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- name: dinov2_Liveness_detection_v2.2.1 |
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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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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/nguyenkhoaht002/liveness_detection/runs/wo6b0psl) |
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# dinov2_Liveness_detection_v2.2.1 |
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This model is a fine-tuned version of [facebook/dinov2-small](https://huggingface.co/facebook/dinov2-small) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0671 |
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- Accuracy: 0.9869 |
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- F1: 0.9868 |
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- Recall: 0.9869 |
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- Precision: 0.9870 |
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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: 5e-05 |
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- train_batch_size: 512 |
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- eval_batch_size: 8 |
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- seed: 42 |
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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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- num_epochs: 5 |
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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 | F1 | Recall | Precision | |
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|:-------------:|:------:|:----:|:---------------:|:--------:|:------:|:------:|:---------:| |
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| 0.183 | 0.8153 | 128 | 0.2473 | 0.9016 | 0.9039 | 0.9016 | 0.9123 | |
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| 0.1022 | 1.6306 | 256 | 0.0750 | 0.9729 | 0.9727 | 0.9729 | 0.9737 | |
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| 0.0432 | 2.4459 | 384 | 0.0575 | 0.9820 | 0.9820 | 0.9820 | 0.9823 | |
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| 0.0247 | 3.2611 | 512 | 0.0507 | 0.9832 | 0.9832 | 0.9832 | 0.9833 | |
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| 0.0115 | 4.0764 | 640 | 0.0536 | 0.9865 | 0.9864 | 0.9865 | 0.9866 | |
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| 0.002 | 4.8917 | 768 | 0.0671 | 0.9869 | 0.9868 | 0.9869 | 0.9870 | |
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### Framework versions |
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- Transformers 4.44.2 |
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- Pytorch 2.4.1+cu121 |
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- Datasets 3.2.0 |
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- Tokenizers 0.19.1 |
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