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README.md
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---
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library_name: peft
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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: vit-base-patch16-224-in21k-finetuned-lora-food101
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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-finetuned-lora-food101
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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: 0.5102
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- Accuracy: 0.8590
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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: 0.005
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- train_batch_size: 128
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- eval_batch_size: 128
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- seed: 42
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- gradient_accumulation_steps: 4
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- total_train_batch_size: 512
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- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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- lr_scheduler_type: linear
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- num_epochs: 5
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- mixed_precision_training: Native AMP
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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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| 0.8294 | 0.9981 | 133 | 0.6474 | 0.8250 |
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| 0.723 | 1.9962 | 266 | 0.5794 | 0.8411 |
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| 0.6554 | 2.9944 | 399 | 0.5468 | 0.8517 |
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| 0.5608 | 4.0 | 533 | 0.5229 | 0.8554 |
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| 0.539 | 4.9906 | 665 | 0.5102 | 0.8590 |
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### Framework versions
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- PEFT 0.13.2
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- Transformers 4.46.3
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- Pytorch 2.5.1+cu121
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- Tokenizers 0.20.3
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