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dinov2-large-MEG6-5
crocutacrocuto/dinov2-large-MEG6-5
dinov2-large-MEG6-5 is a image classification model from crocutacrocuto. Use it when you need a label for an image. It is set up for transformers. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Image Classification
- Library
- transformers
- License
- apache-2.0
- Model type
- dinov2
- Access
- Public
- Created
- Mar 14, 2025
- Updated
- Mar 16, 2025
- SHA
- b9ed73a9
Base models
Model card
From the Hugging Face model README
<!-- 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. -->
dinov2-large-MEG6-5
This model is a fine-tuned version of facebook/dinov2-large on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.2923
- Accuracy: 0.9246
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: 5e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.4129 | 1.0000 | 5156 | 0.4507 | 0.8653 |
| 0.3004 | 1.9999 | 10312 | 0.3710 | 0.8911 |
| 0.1511 | 2.9999 | 15468 | 0.3254 | 0.9078 |
| 0.1183 | 4.0 | 20625 | 0.3185 | 0.9161 |
| 0.0976 | 4.9998 | 25780 | 0.2923 | 0.9246 |
Framework versions
- Transformers 4.46.3
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.20.3
- Task
- Image Classification
- Library
- transformers
- Type
- dinov2
- License
- apache-2.0
- Created
- Mar 14, 2025
- Updated
- Mar 16, 2025