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Plant_Classification_model_vit-base-patch16-224-in21k
Professor/Plant_Classification_model_vit-base-patch16-224-in21k
Plant_Classification_model_vit-base-patch16-224-in21k is a image classification model from Professor. 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
- Dec 9, 2023
- Updated
- Dec 11, 2023
- SHA
- c615c3db
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. -->
Plant_Classification_model_vit-base-patch16-224-in21k
This model is a fine-tuned version of Professor/Plant_Classification_model_vit-base-patch16-224-in21k on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.4976
- Accuracy: 0.8737
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: 0.001
- train_batch_size: 32
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 50
- num_epochs: 20
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 193 | 1.6872 | 0.5531 |
| No log | 2.0 | 386 | 1.2610 | 0.6490 |
| 1.7011 | 3.0 | 579 | 1.1522 | 0.6658 |
| 1.7011 | 4.0 | 772 | 0.9463 | 0.7293 |
| 1.7011 | 5.0 | 965 | 0.8893 | 0.7377 |
| 0.9968 | 6.0 | 1158 | 0.8774 | 0.7306 |
| 0.9968 | 7.0 | 1351 | 0.7006 | 0.7908 |
| 0.734 | 8.0 | 1544 | 0.7599 | 0.7791 |
| 0.734 | 9.0 | 1737 | 0.6890 | 0.7895 |
| 0.734 | 10.0 | 1930 | 0.6686 | 0.7882 |
| 0.5624 | 11.0 | 2123 | 0.6111 | 0.8271 |
| 0.5624 | 12.0 | 2316 | 0.6342 | 0.8122 |
| 0.4342 | 13.0 | 2509 | 0.5493 | 0.8381 |
| 0.4342 | 14.0 | 2702 | 0.5186 | 0.8452 |
| 0.4342 | 15.0 | 2895 | 0.5610 | 0.8381 |
| 0.3097 | 16.0 | 3088 | 0.5520 | 0.8439 |
| 0.3097 | 17.0 | 3281 | 0.5237 | 0.8588 |
| 0.3097 | 18.0 | 3474 | 0.4999 | 0.8659 |
| 0.2119 | 19.0 | 3667 | 0.4976 | 0.8737 |
| 0.2119 | 20.0 | 3860 | 0.5038 | 0.8711 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.0.0
- Datasets 2.15.0
- Tokenizers 0.15.0
- Task
- Image Classification
- Library
- transformers
- Type
- vit
- License
- apache-2.0
- Created
- Dec 9, 2023
- Updated
- Dec 11, 2023