File size: 3,021 Bytes
61765ef 63c1043 61765ef 63c1043 61765ef 63c1043 61765ef 63c1043 18b79b7 61765ef 18b79b7 61765ef 18b79b7 61765ef |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 |
---
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
|