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--- |
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license: apache-2.0 |
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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-railspace |
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results: [] |
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widget: |
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- src: https://huggingface.co/davanstrien/autotrain-mapreader-5000-40830105612/resolve/main/1.png |
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example_title: patch |
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- src: https://huggingface.co/davanstrien/autotrain-mapreader-5000-40830105612/resolve/main/271.png |
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example_title: patch |
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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-beans-demo-v5 |
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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: 0.0292 |
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- Accuracy: 0.9926 |
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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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precision recall f1-score support |
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0 1.00 1.00 1.00 11315 |
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1 0.92 0.94 0.93 204 |
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2 0.95 0.97 0.96 714 |
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3 0.87 0.98 0.92 171 |
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macro avg 0.93 0.97 0.95 12404 |
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weighted avg 0.99 0.99 0.99 12404 |
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accuracy 0.99 12404 |
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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: 64 |
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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 | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:| |
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| 0.0206 | 1.72 | 1000 | 0.0422 | 0.9854 | |
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| 0.0008 | 3.44 | 2000 | 0.0316 | 0.9918 | |
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### Framework versions |
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- Transformers 4.26.1 |
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- Pytorch 1.13.1+cu116 |
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- Datasets 2.10.1 |
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- Tokenizers 0.13.2 |
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