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README.md
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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-base-beans
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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-base-beans
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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: 0.0830
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- Accuracy: 0.9850
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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: 2e-05
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- train_batch_size: 8
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- eval_batch_size: 8
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- seed: 1337
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- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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- lr_scheduler_type: linear
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- num_epochs: 5.0
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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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| 0.2816 | 1.0 | 130 | 0.2185 | 0.9624 |
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| 0.1309 | 2.0 | 260 | 0.1300 | 0.9699 |
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| 0.1404 | 3.0 | 390 | 0.0964 | 0.9774 |
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| 0.0866 | 4.0 | 520 | 0.0628 | 0.9925 |
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| 0.1156 | 5.0 | 650 | 0.0830 | 0.9850 |
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### Framework versions
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- Transformers 4.46.0.dev0
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- Pytorch 2.3.0
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- Datasets 2.19.1
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- Tokenizers 0.20.1
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model.safetensors
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