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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- recall
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- f1
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- precision
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model-index:
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- name: vit-base-16-thesis-demo-PH2
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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-16-thesis-demo-PH2
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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: 0.0761
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- Accuracy: 0.9844
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- Recall: 0.9844
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- F1: 0.9844
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- Precision: 0.9844
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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: 0.0002
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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: 4
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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 | Recall | F1 | Precision |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:------:|:---------:|
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| 0.044 | 2.5 | 50 | 0.0761 | 0.9844 | 0.9844 | 0.9844 | 0.9844 |
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### Framework versions
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- Transformers 4.35.2
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- Pytorch 2.1.0+cu118
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- Datasets 2.15.0
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- Tokenizers 0.15.0
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runs/Dec05_17-52-28_890f1dc26cee/events.out.tfevents.1701798755.890f1dc26cee.296.0
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version https://git-lfs.github.com/spec/v1
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size
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version https://git-lfs.github.com/spec/v1
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size 6286
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