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image_card_classification
inginjadibuparto/image_card_classification
image_card_classification is a machine learning model from inginjadibuparto. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for transformers.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Library
- transformers
- Model type
- resnet
- Access
- Public
- Created
- Mar 8, 2025
- Updated
- Mar 8, 2025
- SHA
- b8ba1f45
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. -->
image_card_classification
This model is a fine-tuned version of on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0612
- Accuracy: 0.9925
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: 0.002
- train_batch_size: 32
- eval_batch_size: 64
- seed: 42
- optimizer: Use OptimizerNames.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: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.1788 | 1.0 | 239 | 1.0625 | 0.6642 |
| 0.6503 | 2.0 | 478 | 0.5765 | 0.8189 |
| 0.3521 | 3.0 | 717 | 0.2616 | 0.9283 |
| 0.2932 | 4.0 | 956 | 0.1590 | 0.9623 |
| 0.1946 | 5.0 | 1195 | 0.1537 | 0.9774 |
| 0.1644 | 6.0 | 1434 | 0.1106 | 0.9774 |
| 0.0438 | 7.0 | 1673 | 0.0697 | 0.9811 |
| 0.0113 | 8.0 | 1912 | 0.0612 | 0.9925 |
| 0.0073 | 9.0 | 2151 | 0.0657 | 0.9887 |
| 0.0105 | 10.0 | 2390 | 0.0550 | 0.9925 |
Framework versions
- Transformers 4.48.3
- Pytorch 2.5.1+cu124
- Tokenizers 0.21.0
- Library
- transformers
- Type
- resnet
- Created
- Mar 8, 2025
- Updated
- Mar 8, 2025