|
--- |
|
language: |
|
- eng |
|
license: apache-2.0 |
|
base_model: facebook/dinov2-large |
|
tags: |
|
- multilabel-image-classification |
|
- multilabel |
|
- generated_from_trainer |
|
metrics: |
|
- accuracy |
|
model-index: |
|
- name: dino-large-2023_12_06-with_custom_head |
|
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-large-2023_12_06-with_custom_head |
|
|
|
This model is a fine-tuned version of [facebook/dinov2-large](https://huggingface.co/facebook/dinov2-large) on the multilabel_complete_dataset dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.2014 |
|
- F1 Micro: 0.8291 |
|
- F1 Macro: 0.8015 |
|
- Roc Auc: 0.9029 |
|
- Accuracy: 0.5132 |
|
- 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: 14 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | F1 Micro | F1 Macro | Roc Auc | Accuracy | Rate | |
|
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:-------:|:--------:|:-----:| |
|
| 0.4706 | 1.0 | 536 | 0.4533 | 0.7389 | 0.6876 | 0.8316 | 0.4269 | 0.01 | |
|
| 0.4045 | 2.0 | 1072 | 0.4262 | 0.7669 | 0.7188 | 0.8634 | 0.4391 | 0.01 | |
|
| 0.3973 | 3.0 | 1608 | 0.4722 | 0.7601 | 0.7176 | 0.8372 | 0.4537 | 0.01 | |
|
| 0.3961 | 4.0 | 2144 | 0.6075 | 0.7528 | 0.6913 | 0.8724 | 0.3762 | 0.01 | |
|
| 0.3751 | 5.0 | 2680 | 0.3916 | 0.7884 | 0.7511 | 0.8925 | 0.4352 | 0.01 | |
|
| 0.365 | 6.0 | 3216 | 0.5256 | 0.7660 | 0.7066 | 0.8535 | 0.4105 | 0.01 | |
|
| 0.3565 | 7.0 | 3752 | 0.5708 | 0.7293 | 0.6947 | 0.8254 | 0.4101 | 0.01 | |
|
| 0.3807 | 8.0 | 4288 | 0.4770 | 0.7811 | 0.7145 | 0.8609 | 0.4591 | 0.01 | |
|
| 0.3462 | 9.0 | 4824 | 0.4612 | 0.7880 | 0.7522 | 0.8775 | 0.4452 | 0.01 | |
|
| 0.38 | 10.0 | 5360 | 0.4559 | 0.7943 | 0.7517 | 0.8747 | 0.4612 | 0.01 | |
|
| 0.3472 | 11.0 | 5896 | 0.5081 | 0.7709 | 0.7315 | 0.8980 | 0.4041 | 0.01 | |
|
| 0.3167 | 12.0 | 6432 | 0.2364 | 0.8268 | 0.7990 | 0.8945 | 0.5141 | 0.001 | |
|
| 0.1322 | 13.0 | 6968 | 0.2222 | 0.8209 | 0.7931 | 0.8951 | 0.4923 | 0.001 | |
|
| 0.0958 | 14.0 | 7504 | 0.2089 | 0.8287 | 0.7975 | 0.8985 | 0.5052 | 0.001 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.34.1 |
|
- Pytorch 2.1.0+cu118 |
|
- Datasets 2.14.5 |
|
- Tokenizers 0.14.1 |
|
|
