transformers pytorch dinov2 multilabel-image-classification multilabel generated_from_trainer eng base_model:facebook/dinov2-large license:apache-2.0 endpoints_compatible region:us
---
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_15-with_custom_head
  results: []
---

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# dino-large-2023_12_15-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: 0.1159
- F1 Micro: 0.8297
- F1 Macro: 0.7800
- Roc Auc: 0.8880
- Accuracy: 0.5435
- 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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1 Micro | F1 Macro | Roc Auc | Accuracy | Rate  |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:-------:|:--------:|:-----:|
| No log        | 1.0   | 268  | 0.1749          | 0.6911   | 0.5979   | 0.7869  | 0.4355   | 0.01  |
| 0.2108        | 2.0   | 536  | 0.1887          | 0.6448   | 0.5545   | 0.7473  | 0.4330   | 0.01  |
| 0.2108        | 3.0   | 804  | 0.1639          | 0.7291   | 0.5960   | 0.8089  | 0.4223   | 0.01  |
| 0.1888        | 4.0   | 1072 | 0.1676          | 0.7426   | 0.6583   | 0.8357  | 0.4416   | 0.01  |
| 0.1888        | 5.0   | 1340 | 0.1619          | 0.7133   | 0.6050   | 0.7932  | 0.4527   | 0.01  |
| 0.1877        | 6.0   | 1608 | 0.1532          | 0.7497   | 0.6624   | 0.8279  | 0.4691   | 0.01  |
| 0.1877        | 7.0   | 1876 | 0.1690          | 0.7409   | 0.6522   | 0.8402  | 0.3758   | 0.01  |
| 0.1845        | 8.0   | 2144 | 0.1461          | 0.7830   | 0.6987   | 0.8601  | 0.4770   | 0.01  |
| 0.1845        | 9.0   | 2412 | 0.1533          | 0.7629   | 0.7143   | 0.8392  | 0.4659   | 0.01  |
| 0.1845        | 10.0  | 2680 | 0.1703          | 0.7335   | 0.6227   | 0.8306  | 0.4234   | 0.01  |
| 0.1845        | 11.0  | 2948 | 0.1714          | 0.7191   | 0.6140   | 0.8054  | 0.4455   | 0.01  |
| 0.1871        | 12.0  | 3216 | 0.1538          | 0.7677   | 0.6816   | 0.8427  | 0.4562   | 0.01  |
| 0.1871        | 13.0  | 3484 | 0.1533          | 0.7673   | 0.6923   | 0.8508  | 0.4573   | 0.01  |
| 0.1881        | 14.0  | 3752 | 0.1572          | 0.7550   | 0.6424   | 0.8395  | 0.4584   | 0.01  |
| 0.1768        | 15.0  | 4020 | 0.1300          | 0.8118   | 0.7646   | 0.8766  | 0.5248   | 0.001 |
| 0.1768        | 16.0  | 4288 | 0.1237          | 0.8229   | 0.7727   | 0.8838  | 0.5277   | 0.001 |
| 0.1499        | 17.0  | 4556 | 0.1218          | 0.8285   | 0.7891   | 0.8933  | 0.5348   | 0.001 |
| 0.1499        | 18.0  | 4824 | 0.1193          | 0.8285   | 0.7831   | 0.8902  | 0.5284   | 0.001 |
| 0.1424        | 19.0  | 5092 | 0.1182          | 0.8298   | 0.7778   | 0.8849  | 0.5445   | 0.001 |
| 0.1424        | 20.0  | 5360 | 0.1182          | 0.8286   | 0.7698   | 0.8827  | 0.5395   | 0.001 |


### Framework versions

- Transformers 4.34.1
- Pytorch 2.1.0+cu118
- Datasets 2.14.5
- Tokenizers 0.14.1
