transformers tensorboard safetensors 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: dinov2-large-2024_01_14-without_data_aug_batch-size32_epochs20_freeze
  results: []
---

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# dinov2-large-2024_01_14-without_data_aug_batch-size32_epochs20_freeze

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: 0.0904
- F1 Micro: 0.8447
- F1 Macro: 0.7156
- Roc Auc: 0.9011
- Accuracy: 0.5459
- Learning Rate: 0.0001

## 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 | Accuracy | F1 Macro | F1 Micro | Validation Loss | Roc Auc | Rate   |
|:-------------:|:-----:|:----:|:--------:|:--------:|:--------:|:---------------:|:-------:|:------:|
| No log        | 1.0   | 274  | 0.4696   | 0.5445   | 0.7663   | 0.1265          | 0.8401  | 0.001  |
| 0.2337        | 2.0   | 548  | 0.5115   | 0.6504   | 0.8026   | 0.1108          | 0.8694  | 0.001  |
| 0.2337        | 3.0   | 822  | 0.5178   | 0.6963   | 0.8184   | 0.1064          | 0.8804  | 0.001  |
| 0.1259        | 4.0   | 1096 | 0.5188   | 0.6838   | 0.8164   | 0.1062          | 0.8808  | 0.001  |
| 0.1259        | 5.0   | 1370 | 0.4965   | 0.6749   | 0.8157   | 0.1069          | 0.8849  | 0.001  |
| 0.1181        | 6.0   | 1644 | 0.5213   | 0.6806   | 0.8223   | 0.1028          | 0.8816  | 0.001  |
| 0.1181        | 7.0   | 1918 | 0.5269   | 0.6718   | 0.8253   | 0.0992          | 0.8857  | 0.001  |
| 0.1146        | 8.0   | 2192 | 0.5216   | 0.6811   | 0.8224   | 0.1004          | 0.8815  | 0.001  |
| 0.1146        | 9.0   | 2466 | 0.5230   | 0.6845   | 0.8302   | 0.1019          | 0.8923  | 0.001  |
| 0.1123        | 10.0  | 2740 | 0.5279   | 0.6775   | 0.8181   | 0.1021          | 0.8754  | 0.001  |
| 0.11          | 11.0  | 3014 | 0.5429   | 0.6897   | 0.8290   | 0.0960          | 0.8815  | 0.001  |
| 0.11          | 12.0  | 3288 | 0.5373   | 0.6825   | 0.8316   | 0.0967          | 0.8896  | 0.001  |
| 0.1098        | 13.0  | 3562 | 0.5328   | 0.6961   | 0.8254   | 0.1009          | 0.8838  | 0.001  |
| 0.1098        | 14.0  | 3836 | 0.0992   | 0.8278   | 0.7092   | 0.8834          | 0.5331  | 0.001  |
| 0.1166        | 15.0  | 4110 | 0.0991   | 0.8230   | 0.6923   | 0.8796          | 0.5335  | 0.001  |
| 0.1166        | 16.0  | 4384 | 0.0918   | 0.8395   | 0.7124   | 0.8932          | 0.5391  | 0.0001 |
| 0.1072        | 17.0  | 4658 | 0.0907   | 0.8439   | 0.7179   | 0.8990          | 0.5471  | 0.0001 |
| 0.1072        | 18.0  | 4932 | 0.0891   | 0.8441   | 0.7237   | 0.8971          | 0.5447  | 0.0001 |
| 0.1017        | 19.0  | 5206 | 0.0892   | 0.8479   | 0.7277   | 0.9027          | 0.5478  | 0.0001 |
| 0.1017        | 20.0  | 5480 | 0.0883   | 0.8484   | 0.7310   | 0.9043          | 0.5509  | 0.0001 |


### Framework versions

- Transformers 4.36.2
- Pytorch 2.1.0+cu118
- Datasets 2.14.5
- Tokenizers 0.15.0
