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_18-kornia_img-size518_batch-size32_epochs20
  results: []
---

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# dino-large-2023_12_18-kornia_img-size518_batch-size32_epochs20

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: 0.1139
- F1 Micro: 0.8312
- F1 Macro: 0.7939
- Roc Auc: 0.8886
- Accuracy: 0.5276
- 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  | 0.1825          | 0.6774   | 0.5984   | 0.7768  | 0.4237   | 0.01  |
| 0.2147        | 2.0   | 536  | 0.1749          | 0.7567   | 0.6636   | 0.8530  | 0.4309   | 0.01  |
| 0.2147        | 3.0   | 804  | 0.1555          | 0.7735   | 0.7210   | 0.8586  | 0.4469   | 0.01  |
| 0.1902        | 4.0   | 1072 | 0.1582          | 0.7546   | 0.6775   | 0.8368  | 0.4469   | 0.01  |
| 0.1902        | 5.0   | 1340 | 0.1599          | 0.7757   | 0.7218   | 0.8741  | 0.4323   | 0.01  |
| 0.1908        | 6.0   | 1608 | 0.1546          | 0.7598   | 0.6469   | 0.8373  | 0.4712   | 0.01  |
| 0.1908        | 7.0   | 1876 | 0.1502          | 0.7747   | 0.7194   | 0.8592  | 0.4566   | 0.01  |
| 0.1871        | 8.0   | 2144 | 0.1542          | 0.7759   | 0.7180   | 0.8669  | 0.4416   | 0.01  |
| 0.1871        | 9.0   | 2412 | 0.1494          | 0.7853   | 0.7134   | 0.8666  | 0.4812   | 0.01  |
| 0.1906        | 10.0  | 2680 | 0.1515          | 0.7530   | 0.6504   | 0.8264  | 0.4673   | 0.01  |
| 0.1906        | 11.0  | 2948 | 0.1578          | 0.7495   | 0.6769   | 0.8296  | 0.4387   | 0.01  |
| 0.1897        | 12.0  | 3216 | 0.1557          | 0.7757   | 0.6902   | 0.8594  | 0.4387   | 0.01  |
| 0.1897        | 13.0  | 3484 | 0.1612          | 0.7293   | 0.6498   | 0.8054  | 0.4530   | 0.01  |
| 0.1879        | 14.0  | 3752 | 0.1800          | 0.6633   | 0.5069   | 0.7571  | 0.4577   | 0.01  |
| 0.1902        | 15.0  | 4020 | 0.1674          | 0.7432   | 0.6672   | 0.8349  | 0.4541   | 0.01  |
| 0.1902        | 16.0  | 4288 | 0.1287          | 0.8137   | 0.7725   | 0.8764  | 0.5177   | 0.001 |
| 0.1612        | 17.0  | 4556 | 0.1246          | 0.8286   | 0.7943   | 0.8927  | 0.5227   | 0.001 |
| 0.1612        | 18.0  | 4824 | 0.1235          | 0.8271   | 0.7885   | 0.8856  | 0.5384   | 0.001 |
| 0.1479        | 19.0  | 5092 | 0.1203          | 0.8366   | 0.8018   | 0.8941  | 0.5423   | 0.001 |
| 0.1479        | 20.0  | 5360 | 0.1148          | 0.8330   | 0.7934   | 0.8852  | 0.5384   | 0.001 |


### Framework versions

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