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convnext-tiny-224-finetuned-cifar10
BeckerAnas/convnext-tiny-224-finetuned-cifar10
convnext-tiny-224-finetuned-cifar10 is a image classification model from BeckerAnas. 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
- convnext
- Access
- Public
- Created
- May 2, 2025
- Updated
- May 16, 2025
- SHA
- f6751cfc
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. -->
convnext-tiny-224-finetuned-cifar10
This model is a fine-tuned version of facebook/convnext-tiny-224 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.1457
- Accuracy: 0.9566
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: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- 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
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.6039 | 1.0 | 352 | 0.2819 | 0.9326 |
| 0.3994 | 2.0 | 704 | 0.1639 | 0.9514 |
| 0.4089 | 2.9922 | 1053 | 0.1455 | 0.9574 |
Framework versions
- Transformers 4.51.3
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.21.1
- Task
- Image Classification
- Library
- transformers
- Type
- convnext
- License
- apache-2.0
- Created
- May 2, 2025
- Updated
- May 16, 2025