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---
language:
- eng
license: apache-2.0
base_model: facebook/dinov2-base
tags:
- image-classification
- multilabel
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: dino-base-2023_11_24-unfreeze
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# dino-base-2023_11_24-unfreeze
This model is a fine-tuned version of [facebook/dinov2-base](https://huggingface.co/facebook/dinov2-base) on the multilabel_complete_dataset dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2045
- F1 Micro: 0.6595
- F1 Macro: 0.5161
- Roc Auc: 0.7681
- Accuracy: 0.2735
- Learning Rate: 0.001
## 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: 0.01
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 30
### Training results
| Training Loss | Epoch | Step | Validation Loss | F1 Micro | F1 Macro | Roc Auc | Accuracy | Rate |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:--------:|:-------:|:--------:|:-----:|
| 0.3961 | 1.0 | 536 | 0.3293 | 0.3296 | 0.0966 | 0.6005 | 0.0736 | 0.01 |
| 0.3418 | 2.0 | 1072 | 0.3382 | 0.3379 | 0.1283 | 0.6054 | 0.0439 | 0.01 |
| 0.3334 | 3.0 | 1608 | 0.3551 | 0.3905 | 0.2420 | 0.6319 | 0.0786 | 0.01 |
| 0.3323 | 4.0 | 2144 | 0.3213 | 0.2555 | 0.1099 | 0.5720 | 0.0625 | 0.01 |
| 0.3248 | 5.0 | 2680 | 0.3164 | 0.3355 | 0.1298 | 0.6024 | 0.0450 | 0.01 |
| 0.3235 | 6.0 | 3216 | 0.3346 | 0.2864 | 0.0806 | 0.5834 | 0.0239 | 0.01 |
| 0.32 | 7.0 | 3752 | 0.3029 | 0.4594 | 0.1968 | 0.6663 | 0.0682 | 0.01 |
| 0.3138 | 8.0 | 4288 | 0.2866 | 0.5468 | 0.2940 | 0.7240 | 0.0579 | 0.01 |
| 0.3052 | 9.0 | 4824 | 0.2807 | 0.4767 | 0.2993 | 0.6672 | 0.1225 | 0.01 |
| 0.3157 | 10.0 | 5360 | 0.2955 | 0.4752 | 0.2091 | 0.6733 | 0.0707 | 0.01 |
| 0.3119 | 11.0 | 5896 | 0.3405 | 0.4028 | 0.2160 | 0.6336 | 0.1361 | 0.01 |
| 0.3162 | 12.0 | 6432 | 0.4163 | 0.4899 | 0.2965 | 0.6863 | 0.0532 | 0.01 |
| 0.3184 | 13.0 | 6968 | 0.2964 | 0.5429 | 0.3299 | 0.7170 | 0.1047 | 0.01 |
| 0.3142 | 14.0 | 7504 | 0.3005 | 0.5253 | 0.3154 | 0.7072 | 0.0832 | 0.01 |
| 0.3104 | 15.0 | 8040 | 3.1991 | 0.1673 | 0.0674 | 0.4879 | 0.0 | 0.01 |
| 0.3042 | 16.0 | 8576 | 0.2820 | 0.4544 | 0.2746 | 0.6519 | 0.1583 | 0.001 |
| 0.2788 | 17.0 | 9112 | 0.2741 | 0.5744 | 0.3842 | 0.7205 | 0.1640 | 0.001 |
| 0.2724 | 18.0 | 9648 | 0.2424 | 0.5903 | 0.3936 | 0.7256 | 0.2072 | 0.001 |
| 0.2642 | 19.0 | 10184 | 0.2414 | 0.6021 | 0.4095 | 0.7347 | 0.2186 | 0.001 |
| 0.2597 | 20.0 | 10720 | 0.2269 | 0.6079 | 0.4156 | 0.7347 | 0.2251 | 0.001 |
| 0.2575 | 21.0 | 11256 | 0.2249 | 0.6231 | 0.4253 | 0.7463 | 0.2340 | 0.001 |
| 0.253 | 22.0 | 11792 | 0.2261 | 0.6291 | 0.4639 | 0.7521 | 0.2429 | 0.001 |
| 0.2491 | 23.0 | 12328 | 0.2163 | 0.6454 | 0.4856 | 0.7627 | 0.2537 | 0.001 |
| 0.2484 | 24.0 | 12864 | 0.2212 | 0.6262 | 0.4635 | 0.7460 | 0.2569 | 0.001 |
| 0.2465 | 25.0 | 13400 | 0.2118 | 0.6486 | 0.4780 | 0.7622 | 0.2772 | 0.001 |
| 0.241 | 26.0 | 13936 | 0.2106 | 0.6602 | 0.5159 | 0.7727 | 0.2558 | 0.001 |
| 0.2413 | 27.0 | 14472 | 0.2135 | 0.6390 | 0.4979 | 0.7536 | 0.2722 | 0.001 |
| 0.2385 | 28.0 | 15008 | 0.2182 | 0.6103 | 0.4596 | 0.7319 | 0.2772 | 0.001 |
| 0.2366 | 29.0 | 15544 | 0.2132 | 0.6615 | 0.5354 | 0.7758 | 0.2708 | 0.001 |
| 0.2345 | 30.0 | 16080 | 0.2069 | 0.6566 | 0.5122 | 0.7658 | 0.2747 | 0.001 |
### Framework versions
- Transformers 4.34.1
- Pytorch 2.1.0+cu118
- Datasets 2.14.5
- Tokenizers 0.14.1
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