VectorZhao
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README.md
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---
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license: apache-2.0
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base_model: google/vit-base-patch16-224
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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-oxford-iiit-pets
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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-oxford-iiit-pets
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This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.2028
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- Accuracy: 0.9405
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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: 0.0003
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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: 5
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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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| 0.3749 | 1.0 | 370 | 0.2825 | 0.9364 |
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| 0.2117 | 2.0 | 740 | 0.2231 | 0.9418 |
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| 0.1831 | 3.0 | 1110 | 0.1963 | 0.9472 |
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| 0.1449 | 4.0 | 1480 | 0.1913 | 0.9486 |
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| 0.1312 | 5.0 | 1850 | 0.1866 | 0.9445 |
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### Framework versions
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- Transformers 4.41.2
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- Pytorch 2.3.0+cu121
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- Datasets 2.20.0
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- Tokenizers 0.19.1
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runs/Jul05_08-23-45_8ebef051db4c/events.out.tfevents.1720168432.8ebef051db4c.10804.6
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version https://git-lfs.github.com/spec/v1
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oid sha256:a4c3af9054652c587006c2544ec9966ad77d400324ea3b82506dbac8e4985b9a
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size 411
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