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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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metrics:
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- accuracy
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model-index:
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- name: vit-base-patch16-224-in21k-shiba-inu-detector
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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-patch16-224-in21k-shiba-inu-detector
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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: 0.1930
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- Accuracy: 1.0
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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: 5e-05
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- train_batch_size: 32
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- eval_batch_size: 32
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- seed: 42
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- gradient_accumulation_steps: 4
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- total_train_batch_size: 128
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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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- lr_scheduler_warmup_ratio: 0.1
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- num_epochs: 20
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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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| No log | 0.94 | 4 | 1.3875 | 0.1667 |
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| No log | 1.94 | 8 | 1.2712 | 0.7833 |
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| 1.4176 | 2.94 | 12 | 1.0972 | 0.9 |
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| 1.4176 | 3.94 | 16 | 0.9365 | 0.95 |
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| 1.0144 | 4.94 | 20 | 0.7836 | 0.9833 |
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| 1.0144 | 5.94 | 24 | 0.6511 | 1.0 |
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| 1.0144 | 6.94 | 28 | 0.5329 | 1.0 |
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| 0.6329 | 7.94 | 32 | 0.4403 | 1.0 |
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| 0.6329 | 8.94 | 36 | 0.3777 | 1.0 |
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| 0.3821 | 9.94 | 40 | 0.3273 | 1.0 |
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| 0.3821 | 10.94 | 44 | 0.2886 | 1.0 |
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| 0.3821 | 11.94 | 48 | 0.2622 | 1.0 |
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| 0.2655 | 12.94 | 52 | 0.2397 | 1.0 |
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| 0.2655 | 13.94 | 56 | 0.2250 | 1.0 |
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| 0.202 | 14.94 | 60 | 0.2152 | 1.0 |
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| 0.202 | 15.94 | 64 | 0.2074 | 1.0 |
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| 0.202 | 16.94 | 68 | 0.2003 | 1.0 |
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| 0.1785 | 17.94 | 72 | 0.1960 | 1.0 |
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| 0.1785 | 18.94 | 76 | 0.1936 | 1.0 |
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| 0.1618 | 19.94 | 80 | 0.1930 | 1.0 |
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### Framework versions
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- Transformers 4.17.0
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- Pytorch 1.11.0+cu113
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- Datasets 2.0.0
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- Tokenizers 0.11.6
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