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language: |
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- eng |
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license: apache-2.0 |
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base_model: facebook/dinov2-large |
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tags: |
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- multilabel-image-classification |
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- multilabel |
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- generated_from_trainer |
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metrics: |
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- accuracy |
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model-index: |
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- name: dinov2-large-2024_01_14-without_data_aug_batch-size32_epochs20_freeze |
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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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# dinov2-large-2024_01_14-without_data_aug_batch-size32_epochs20_freeze |
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This model is a fine-tuned version of [facebook/dinov2-large](https://huggingface.co/facebook/dinov2-large) on the multilabel_complete_dataset dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0904 |
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- F1 Micro: 0.8447 |
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- F1 Macro: 0.7156 |
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- Roc Auc: 0.9011 |
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- Accuracy: 0.5459 |
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- Learning Rate: 0.0001 |
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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: 0.01 |
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- train_batch_size: 32 |
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- eval_batch_size: 32 |
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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: 20 |
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### Training results |
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| Training Loss | Epoch | Step | Accuracy | F1 Macro | F1 Micro | Validation Loss | Roc Auc | Rate | |
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|:-------------:|:-----:|:----:|:--------:|:--------:|:--------:|:---------------:|:-------:|:------:| |
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| No log | 1.0 | 274 | 0.4696 | 0.5445 | 0.7663 | 0.1265 | 0.8401 | 0.001 | |
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| 0.2337 | 2.0 | 548 | 0.5115 | 0.6504 | 0.8026 | 0.1108 | 0.8694 | 0.001 | |
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| 0.2337 | 3.0 | 822 | 0.5178 | 0.6963 | 0.8184 | 0.1064 | 0.8804 | 0.001 | |
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| 0.1259 | 4.0 | 1096 | 0.5188 | 0.6838 | 0.8164 | 0.1062 | 0.8808 | 0.001 | |
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| 0.1259 | 5.0 | 1370 | 0.4965 | 0.6749 | 0.8157 | 0.1069 | 0.8849 | 0.001 | |
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| 0.1181 | 6.0 | 1644 | 0.5213 | 0.6806 | 0.8223 | 0.1028 | 0.8816 | 0.001 | |
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| 0.1181 | 7.0 | 1918 | 0.5269 | 0.6718 | 0.8253 | 0.0992 | 0.8857 | 0.001 | |
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| 0.1146 | 8.0 | 2192 | 0.5216 | 0.6811 | 0.8224 | 0.1004 | 0.8815 | 0.001 | |
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| 0.1146 | 9.0 | 2466 | 0.5230 | 0.6845 | 0.8302 | 0.1019 | 0.8923 | 0.001 | |
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| 0.1123 | 10.0 | 2740 | 0.5279 | 0.6775 | 0.8181 | 0.1021 | 0.8754 | 0.001 | |
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| 0.11 | 11.0 | 3014 | 0.5429 | 0.6897 | 0.8290 | 0.0960 | 0.8815 | 0.001 | |
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| 0.11 | 12.0 | 3288 | 0.5373 | 0.6825 | 0.8316 | 0.0967 | 0.8896 | 0.001 | |
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| 0.1098 | 13.0 | 3562 | 0.5328 | 0.6961 | 0.8254 | 0.1009 | 0.8838 | 0.001 | |
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| 0.1098 | 14.0 | 3836 | 0.0992 | 0.8278 | 0.7092 | 0.8834 | 0.5331 | 0.001 | |
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| 0.1166 | 15.0 | 4110 | 0.0991 | 0.8230 | 0.6923 | 0.8796 | 0.5335 | 0.001 | |
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| 0.1166 | 16.0 | 4384 | 0.0918 | 0.8395 | 0.7124 | 0.8932 | 0.5391 | 0.0001 | |
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| 0.1072 | 17.0 | 4658 | 0.0907 | 0.8439 | 0.7179 | 0.8990 | 0.5471 | 0.0001 | |
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| 0.1072 | 18.0 | 4932 | 0.0891 | 0.8441 | 0.7237 | 0.8971 | 0.5447 | 0.0001 | |
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| 0.1017 | 19.0 | 5206 | 0.0892 | 0.8479 | 0.7277 | 0.9027 | 0.5478 | 0.0001 | |
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| 0.1017 | 20.0 | 5480 | 0.0883 | 0.8484 | 0.7310 | 0.9043 | 0.5509 | 0.0001 | |
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### Framework versions |
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- Transformers 4.36.2 |
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- Pytorch 2.1.0+cu118 |
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- Datasets 2.14.5 |
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- Tokenizers 0.15.0 |
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