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-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: food101-vit-base-patch16-224-in21k
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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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# food101-vit-base-patch16-224-in21k
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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: 0.3894
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- Accuracy: 0.9072
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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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| 0.9431 | 1.0 | 9469 | 0.6777 | 0.8593 |
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| 0.617 | 2.0 | 18938 | 0.4546 | 0.8802 |
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| 0.9109 | 3.0 | 28407 | 0.4086 | 0.8899 |
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| 1.0346 | 4.0 | 37876 | 0.3911 | 0.8968 |
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| 0.2142 | 5.0 | 47345 | 0.4098 | 0.8913 |
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| 0.7247 | 6.0 | 56814 | 0.3904 | 0.9008 |
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| 0.3935 | 7.0 | 66283 | 0.3873 | 0.9035 |
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| 0.552 | 8.0 | 75752 | 0.3915 | 0.9053 |
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| 0.4012 | 9.0 | 85221 | 0.3955 | 0.9052 |
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| 0.2699 | 10.0 | 94690 | 0.3894 | 0.9072 |
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### Framework versions
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- Transformers 4.38.0
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- Pytorch 2.1.2+cu118
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- Datasets 2.19.1
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- Tokenizers 0.15.2
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model.safetensors
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