Model save
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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: 0.2148
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- Accuracy: 0.9418
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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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| 0.3959 | 1.0 | 370 | 0.2667 | 0.9364 |
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| 0.193 | 2.0 | 740 | 0.2010 | 0.9445 |
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| 0.1665 | 3.0 | 1110 | 0.1798 | 0.9499 |
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| 0.14 | 4.0 | 1480 | 0.1692 | 0.9526 |
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| 0.1367 | 5.0 | 1850 | 0.1682 | 0.9499 |
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### Framework versions
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- Transformers 4.40.1
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- Pytorch 2.2.1
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- Datasets 2.16.1
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- Tokenizers 0.19.1
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runs/May12_21-14-26_machinelearning/events.out.tfevents.1715563506.machinelearning.754853.1
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version https://git-lfs.github.com/spec/v1
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oid sha256:7580051583957bca680d8dd7333132a7aeefdc7db24ac52424f74cafa7ad3ab9
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size 411
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