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Mangovariety
Docty/Mangovariety
Mangovariety is a image classification model from Docty. 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
- vit
- Access
- Public
- Created
- Apr 14, 2025
- Updated
- Apr 14, 2025
- SHA
- aa05bcb6
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. -->
mango_output12
This model is a fine-tuned version of google/vit-base-patch16-224-in21k on the Docty/Mangovariety dataset. It achieves the following results on the evaluation set:
- Loss: 0.3909
- Accuracy: 0.9917
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: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 1337
- 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: 5.0
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 85 | 1.2826 | 0.9375 |
| No log | 2.0 | 170 | 0.7519 | 0.975 |
| No log | 3.0 | 255 | 0.5236 | 0.9792 |
| No log | 4.0 | 340 | 0.4190 | 0.9875 |
| No log | 5.0 | 425 | 0.3909 | 0.9917 |
Framework versions
- Transformers 4.51.1
- Pytorch 2.5.1+cu124
- Datasets 3.5.0
- Tokenizers 0.21.0
- Task
- Image Classification
- Library
- transformers
- Type
- vit
- License
- apache-2.0
- Created
- Apr 14, 2025
- Updated
- Apr 14, 2025