zhoadk/vit-base-patch16-224-in21k-finetuned-lora-food101
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README.md
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---
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base_model: google/vit-base-patch16-224-in21k
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library_name: peft
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license: apache-2.0
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metrics:
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- accuracy
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tags:
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- generated_from_trainer
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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: 0.0744
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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: 0.005
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- train_batch_size: 64
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- eval_batch_size: 64
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- seed: 42
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- gradient_accumulation_steps: 4
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- total_train_batch_size: 256
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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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- 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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| No log | 0.8 | 3 | 2.2155 | 0.99 |
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| No log | 1.8667 | 7 | 0.3241 | 0.98 |
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| 1.7947 | 2.9333 | 11 | 0.1304 | 0.98 |
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| 1.7947 | 4.0 | 15 | 0.0744 | 1.0 |
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### Framework versions
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- PEFT 0.13.2
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- Transformers 4.44.2
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- Pytorch 2.4.1+cu121
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- Datasets 3.0.1
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- Tokenizers 0.19.1
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runs/Oct17_11-35-47_d41f08a65555/events.out.tfevents.1729164949.d41f08a65555.56041.0
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version https://git-lfs.github.com/spec/v1
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oid sha256:
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size
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version https://git-lfs.github.com/spec/v1
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oid sha256:74d9348cf6db8e170c6f9dcb6d4279d76c06826d9426b0e6c909cf5c9f588447
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size 11535
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