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train_dit02_initials_3cat_cls_3.5k_naflex
distill-lab/train_dit02_initials_3cat_cls_3.5k_naflex
train_dit02_initials_3cat_cls_3.5k_naflex is a image classification model from distill-lab. 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
- siglip2
- Access
- Public
- Created
- Oct 13, 2025
- Updated
- Oct 13, 2025
- SHA
- 935ed02d
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. -->
train_dit02_initials_3cat_cls_3.5k_naflex
This model is a fine-tuned version of google/siglip2-so400m-patch16-naflex on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 2.2541
- Accuracy: 0.6474
- Precision: 0.6451
- Recall: 0.6474
- F1: 0.6312
- Roc Auc: 0.7542
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-06
- train_batch_size: 64
- eval_batch_size: 64
- seed: 1337
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- num_epochs: 20.0
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | Roc Auc |
|---|---|---|---|---|---|---|---|---|
| 0.1606 | 2.0833 | 100 | 0.2993 | 0.6530 | 0.6537 | 0.6530 | 0.6395 | 0.7772 |
| 0.0511 | 4.1667 | 200 | 0.6150 | 0.6101 | 0.6770 | 0.6101 | 0.6038 | 0.7704 |
| 0.0104 | 6.25 | 300 | 0.7966 | 0.6549 | 0.6360 | 0.6549 | 0.6394 | 0.7630 |
| 0.0114 | 8.3333 | 400 | 0.9993 | 0.6604 | 0.6599 | 0.6604 | 0.6489 | 0.7559 |
| 0.0016 | 10.4167 | 500 | 1.2927 | 0.6530 | 0.6350 | 0.6530 | 0.6267 | 0.7524 |
| 0.0002 | 12.5 | 600 | 1.4876 | 0.6287 | 0.6400 | 0.6287 | 0.6162 | 0.7600 |
| 0.0 | 14.5833 | 700 | 2.0675 | 0.6455 | 0.6336 | 0.6455 | 0.6271 | 0.7547 |
| 0.0 | 16.6667 | 800 | 2.1974 | 0.6493 | 0.6390 | 0.6493 | 0.6305 | 0.7562 |
| 0.0 | 18.75 | 900 | 2.2512 | 0.6493 | 0.6473 | 0.6493 | 0.6331 | 0.7541 |
Framework versions
- Transformers 4.56.2
- Pytorch 2.7.1+cu126
- Datasets 4.0.0
- Tokenizers 0.22.1
- Task
- Image Classification
- Library
- transformers
- Type
- siglip2
- License
- apache-2.0
- Created
- Oct 13, 2025
- Updated
- Oct 13, 2025