--- license: apache-2.0 base_model: facebook/dinov2-large tags: - generated_from_trainer metrics: - accuracy model-index: - name: drone_DinoVdeau-large-2024_09_18-batch-size64_epochs100_freeze results: [] --- # drone_DinoVdeau-large-2024_09_18-batch-size64_epochs100_freeze This model is a fine-tuned version of [facebook/dinov2-large](https://huggingface.co/facebook/dinov2-large) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.2981 - F1 Micro: 0.8388 - F1 Macro: 0.6139 - Roc Auc: 0.8667 - Accuracy: 0.2677 - Learning Rate: 1e-05 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.001 - train_batch_size: 64 - eval_batch_size: 64 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 100 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | F1 Micro | F1 Macro | Roc Auc | Accuracy | Rate | |:-------------:|:-----:|:-----:|:---------------:|:--------:|:--------:|:-------:|:--------:|:------:| | No log | 1.0 | 181 | 0.3341 | 0.8203 | 0.5745 | 0.8508 | 0.2409 | 0.001 | | No log | 2.0 | 362 | 0.3186 | 0.8327 | 0.5964 | 0.8618 | 0.2401 | 0.001 | | 0.41 | 3.0 | 543 | 0.3190 | 0.8323 | 0.5896 | 0.8611 | 0.2516 | 0.001 | | 0.41 | 4.0 | 724 | 0.3149 | 0.8322 | 0.5800 | 0.8608 | 0.2573 | 0.001 | | 0.41 | 5.0 | 905 | 0.3153 | 0.8314 | 0.5992 | 0.8601 | 0.2526 | 0.001 | | 0.3412 | 6.0 | 1086 | 0.3147 | 0.8368 | 0.6059 | 0.8655 | 0.2505 | 0.001 | | 0.3412 | 7.0 | 1267 | 0.3130 | 0.8297 | 0.5672 | 0.8583 | 0.2643 | 0.001 | | 0.3412 | 8.0 | 1448 | 0.3127 | 0.8305 | 0.5794 | 0.8590 | 0.2643 | 0.001 | | 0.3338 | 9.0 | 1629 | 0.3131 | 0.8327 | 0.5719 | 0.8608 | 0.2700 | 0.001 | | 0.3338 | 10.0 | 1810 | 0.3097 | 0.8355 | 0.5897 | 0.8638 | 0.2518 | 0.001 | | 0.3338 | 11.0 | 1991 | 0.3123 | 0.8332 | 0.5735 | 0.8612 | 0.2742 | 0.001 | | 0.3303 | 12.0 | 2172 | 0.3085 | 0.8331 | 0.5806 | 0.8612 | 0.2706 | 0.001 | | 0.3303 | 13.0 | 2353 | 0.3079 | 0.8348 | 0.5952 | 0.8628 | 0.2646 | 0.001 | | 0.3278 | 14.0 | 2534 | 0.3165 | 0.8340 | 0.5969 | 0.8626 | 0.2534 | 0.001 | | 0.3278 | 15.0 | 2715 | 0.3074 | 0.8351 | 0.5790 | 0.8631 | 0.2760 | 0.001 | | 0.3278 | 16.0 | 2896 | 0.3095 | 0.8356 | 0.5889 | 0.8637 | 0.2635 | 0.001 | | 0.3273 | 17.0 | 3077 | 0.3103 | 0.8395 | 0.6138 | 0.8680 | 0.2474 | 0.001 | | 0.3273 | 18.0 | 3258 | 0.3063 | 0.8334 | 0.5715 | 0.8611 | 0.2763 | 0.001 | | 0.3273 | 19.0 | 3439 | 0.3110 | 0.8337 | 0.5920 | 0.8617 | 0.2656 | 0.001 | | 0.324 | 20.0 | 3620 | 0.3072 | 0.8375 | 0.5984 | 0.8655 | 0.2596 | 0.001 | | 0.324 | 21.0 | 3801 | 0.3074 | 0.8389 | 0.6090 | 0.8672 | 0.2560 | 0.001 | | 0.324 | 22.0 | 3982 | 0.3070 | 0.8355 | 0.5808 | 0.8634 | 0.2656 | 0.001 | | 0.3263 | 23.0 | 4163 | 0.3077 | 0.8389 | 0.6160 | 0.8669 | 0.2627 | 0.001 | | 0.3263 | 24.0 | 4344 | 0.3061 | 0.8363 | 0.5881 | 0.8640 | 0.2656 | 0.001 | | 0.3244 | 25.0 | 4525 | 0.3043 | 0.8402 | 0.6102 | 0.8679 | 0.2664 | 0.001 | | 0.3244 | 26.0 | 4706 | 0.3110 | 0.8327 | 0.5806 | 0.8610 | 0.2659 | 0.001 | | 0.3244 | 27.0 | 4887 | 0.3052 | 0.8380 | 0.5850 | 0.8656 | 0.2713 | 0.001 | | 0.3257 | 28.0 | 5068 | 0.3030 | 0.8397 | 0.5974 | 0.8674 | 0.2664 | 0.001 | | 0.3257 | 29.0 | 5249 | 0.3067 | 0.8362 | 0.5902 | 0.8642 | 0.2666 | 0.001 | | 0.3257 | 30.0 | 5430 | 0.3061 | 0.8363 | 0.5924 | 0.8644 | 0.2635 | 0.001 | | 0.3243 | 31.0 | 5611 | 0.3028 | 0.8373 | 0.5867 | 0.8649 | 0.2708 | 0.001 | | 0.3243 | 32.0 | 5792 | 0.3060 | 0.8388 | 0.6094 | 0.8667 | 0.2568 | 0.001 | | 0.3243 | 33.0 | 5973 | 0.3069 | 0.8342 | 0.5866 | 0.8625 | 0.2651 | 0.001 | | 0.3257 | 34.0 | 6154 | 0.3069 | 0.8363 | 0.5901 | 0.8641 | 0.2664 | 0.001 | | 0.3257 | 35.0 | 6335 | 0.3041 | 0.8380 | 0.6009 | 0.8657 | 0.2627 | 0.001 | | 0.324 | 36.0 | 6516 | 0.3045 | 0.8363 | 0.5947 | 0.8640 | 0.2661 | 0.001 | | 0.324 | 37.0 | 6697 | 0.3037 | 0.8396 | 0.5995 | 0.8672 | 0.2760 | 0.001 | | 0.324 | 38.0 | 6878 | 0.3015 | 0.8388 | 0.5860 | 0.8662 | 0.2737 | 0.0001 | | 0.3203 | 39.0 | 7059 | 0.3005 | 0.8381 | 0.5995 | 0.8656 | 0.2737 | 0.0001 | | 0.3203 | 40.0 | 7240 | 0.3010 | 0.8417 | 0.6126 | 0.8692 | 0.2695 | 0.0001 | | 0.3203 | 41.0 | 7421 | 0.2990 | 0.8403 | 0.6073 | 0.8677 | 0.2742 | 0.0001 | | 0.3165 | 42.0 | 7602 | 0.2996 | 0.8409 | 0.5992 | 0.8681 | 0.2713 | 0.0001 | | 0.3165 | 43.0 | 7783 | 0.2986 | 0.8414 | 0.6092 | 0.8688 | 0.2695 | 0.0001 | | 0.3165 | 44.0 | 7964 | 0.2982 | 0.8396 | 0.5954 | 0.8668 | 0.2750 | 0.0001 | | 0.3138 | 45.0 | 8145 | 0.2977 | 0.8401 | 0.6028 | 0.8674 | 0.2758 | 0.0001 | | 0.3138 | 46.0 | 8326 | 0.2982 | 0.8406 | 0.5966 | 0.8677 | 0.2755 | 0.0001 | | 0.3125 | 47.0 | 8507 | 0.2997 | 0.8378 | 0.5893 | 0.8650 | 0.2768 | 0.0001 | | 0.3125 | 48.0 | 8688 | 0.2978 | 0.8420 | 0.6135 | 0.8694 | 0.2747 | 0.0001 | | 0.3125 | 49.0 | 8869 | 0.2981 | 0.8399 | 0.6017 | 0.8671 | 0.2747 | 0.0001 | | 0.312 | 50.0 | 9050 | 0.2977 | 0.8410 | 0.6113 | 0.8684 | 0.2703 | 0.0001 | | 0.312 | 51.0 | 9231 | 0.3001 | 0.8419 | 0.6110 | 0.8696 | 0.2716 | 0.0001 | | 0.312 | 52.0 | 9412 | 0.2977 | 0.8380 | 0.6011 | 0.8653 | 0.2789 | 0.0001 | | 0.3115 | 53.0 | 9593 | 0.2966 | 0.8425 | 0.6151 | 0.8699 | 0.2729 | 0.0001 | | 0.3115 | 54.0 | 9774 | 0.2977 | 0.8399 | 0.5974 | 0.8669 | 0.2810 | 0.0001 | | 0.3115 | 55.0 | 9955 | 0.2965 | 0.8407 | 0.6119 | 0.8680 | 0.2724 | 0.0001 | | 0.3105 | 56.0 | 10136 | 0.2966 | 0.8408 | 0.6058 | 0.8679 | 0.2786 | 0.0001 | | 0.3105 | 57.0 | 10317 | 0.2978 | 0.8399 | 0.6068 | 0.8672 | 0.2747 | 0.0001 | | 0.3105 | 58.0 | 10498 | 0.2965 | 0.8427 | 0.6146 | 0.8699 | 0.2721 | 0.0001 | | 0.3105 | 59.0 | 10679 | 0.2961 | 0.8406 | 0.6006 | 0.8676 | 0.2794 | 0.0001 | | 0.3105 | 60.0 | 10860 | 0.2961 | 0.8429 | 0.6113 | 0.8700 | 0.2797 | 0.0001 | | 0.308 | 61.0 | 11041 | 0.2963 | 0.8415 | 0.5999 | 0.8684 | 0.2797 | 0.0001 | | 0.308 | 62.0 | 11222 | 0.2961 | 0.8405 | 0.6017 | 0.8676 | 0.2789 | 0.0001 | | 0.308 | 63.0 | 11403 | 0.2955 | 0.8421 | 0.6108 | 0.8693 | 0.2737 | 0.0001 | | 0.3083 | 64.0 | 11584 | 0.2952 | 0.8407 | 0.6127 | 0.8679 | 0.2791 | 0.0001 | | 0.3083 | 65.0 | 11765 | 0.2984 | 0.8391 | 0.6022 | 0.8664 | 0.2781 | 0.0001 | | 0.3083 | 66.0 | 11946 | 0.2957 | 0.8415 | 0.6104 | 0.8687 | 0.2739 | 0.0001 | | 0.3051 | 67.0 | 12127 | 0.2962 | 0.8416 | 0.6142 | 0.8690 | 0.2760 | 0.0001 | | 0.3051 | 68.0 | 12308 | 0.2967 | 0.8413 | 0.6084 | 0.8686 | 0.2773 | 0.0001 | | 0.3051 | 69.0 | 12489 | 0.2960 | 0.8406 | 0.6161 | 0.8679 | 0.2729 | 0.0001 | | 0.3066 | 70.0 | 12670 | 0.2972 | 0.8434 | 0.6248 | 0.8708 | 0.2682 | 0.0001 | | 0.3066 | 71.0 | 12851 | 0.2965 | 0.8396 | 0.6081 | 0.8668 | 0.2802 | 1e-05 | | 0.3061 | 72.0 | 13032 | 0.2961 | 0.8422 | 0.6034 | 0.8691 | 0.2807 | 1e-05 | | 0.3061 | 73.0 | 13213 | 0.2954 | 0.8409 | 0.6080 | 0.8679 | 0.2810 | 1e-05 | | 0.3061 | 74.0 | 13394 | 0.2954 | 0.8411 | 0.6093 | 0.8682 | 0.2810 | 1e-05 | ### Framework versions - Transformers 4.41.1 - Pytorch 2.3.0+cu121 - Datasets 2.19.1 - Tokenizers 0.19.1