---
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