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End of training
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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: vit-base-patch16-224-in21k-cards-base-classifier-defects-finder
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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-cards-base-classifier-defects-finder
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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 the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.0683
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- Accuracy: 0.999
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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: 5e-05
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- train_batch_size: 32
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- eval_batch_size: 32
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- seed: 42
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- gradient_accumulation_steps: 4
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- total_train_batch_size: 128
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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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- lr_scheduler_warmup_ratio: 0.1
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- num_epochs: 10
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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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| 1.4892 | 0.9929 | 70 | 1.3366 | 0.859 |
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| 0.4362 | 2.0 | 141 | 0.4142 | 0.971 |
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| 0.231 | 2.9929 | 211 | 0.2250 | 0.988 |
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| 0.1654 | 4.0 | 282 | 0.1687 | 0.982 |
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| 0.1289 | 4.9929 | 352 | 0.1322 | 0.991 |
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| 0.0999 | 6.0 | 423 | 0.1184 | 0.988 |
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| 0.0824 | 6.9929 | 493 | 0.0852 | 0.996 |
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| 0.0789 | 8.0 | 564 | 0.0809 | 0.998 |
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| 0.07 | 8.9929 | 634 | 0.0723 | 0.997 |
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| 0.067 | 9.9291 | 700 | 0.0683 | 0.999 |
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### Framework versions
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- Transformers 4.41.2
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- Pytorch 2.0.1+cu117
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- Datasets 2.19.2
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- Tokenizers 0.19.1
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