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---
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library_name: transformers
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license: apache-2.0
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base_model: google/vit-base-patch16-224-in21k
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tags:
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- generated_from_trainer
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metrics:
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- accuracy
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model-index:
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- name: ViT_Cucumber
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# ViT_Cucumber
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This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.0155
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- Accuracy: 0.9976
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 0.0002
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- train_batch_size: 16
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- eval_batch_size: 8
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- seed: 42
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- num_epochs: 4
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- mixed_precision_training: Native AMP
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy |
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|:-------------:|:------:|:----:|:---------------:|:--------:|
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| 0.1694 | 0.3571 | 100 | 0.1965 | 0.9607 |
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| 0.1409 | 0.7143 | 200 | 0.2409 | 0.9261 |
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| 0.1024 | 1.0714 | 300 | 0.0903 | 0.9780 |
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| 0.0326 | 1.4286 | 400 | 0.0630 | 0.9866 |
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| 0.0338 | 1.7857 | 500 | 0.0675 | 0.9843 |
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| 0.0082 | 2.1429 | 600 | 0.0508 | 0.9882 |
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| 0.0072 | 2.5 | 700 | 0.0609 | 0.9874 |
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| 0.0056 | 2.8571 | 800 | 0.0175 | 0.9976 |
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| 0.0044 | 3.2143 | 900 | 0.0154 | 0.9976 |
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| 0.0042 | 3.5714 | 1000 | 0.0151 | 0.9976 |
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| 0.0045 | 3.9286 | 1100 | 0.0155 | 0.9976 |
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### Framework versions
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- Transformers 4.44.2
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- Pytorch 2.3.0+cu118
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- Datasets 3.2.0
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- Tokenizers 0.19.1
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