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README.md
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---
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license: apache-2.0
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tags:
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- generated_from_trainer
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datasets:
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- gtsrb
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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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- task:
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name: Image Classification
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type: image-classification
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dataset:
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name: gtsrb
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type: gtsrb
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args: gtsrb
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metrics:
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- name: Accuracy
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type: accuracy
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value: 0.9989799387963277
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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 the gtsrb dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.0038
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- Accuracy: 0.9990
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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: 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: 10.0
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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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| 0.2593 | 1.0 | 4166 | 0.1585 | 0.9697 |
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| 0.2659 | 2.0 | 8332 | 0.0472 | 0.9900 |
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| 0.2825 | 3.0 | 12498 | 0.0155 | 0.9971 |
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| 0.0953 | 4.0 | 16664 | 0.0113 | 0.9983 |
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| 0.1277 | 5.0 | 20830 | 0.0076 | 0.9985 |
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| 0.0816 | 6.0 | 24996 | 0.0047 | 0.9988 |
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| 0.0382 | 7.0 | 29162 | 0.0041 | 0.9990 |
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| 0.0983 | 8.0 | 33328 | 0.0059 | 0.9990 |
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| 0.1746 | 9.0 | 37494 | 0.0034 | 0.9993 |
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| 0.1153 | 10.0 | 41660 | 0.0038 | 0.9990 |
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### Framework versions
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- Transformers 4.21.0.dev0
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- Pytorch 1.12.0
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- Datasets 2.3.2
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- Tokenizers 0.12.1
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