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---
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library_name: transformers
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license: apache-2.0
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base_model: google/vit-base-patch16-384
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tags:
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- generated_from_trainer
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metrics:
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- precision
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- recall
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- f1
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model-index:
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- name: segmented-augmented
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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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# segmented-augmented
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This model is a fine-tuned version of [google/vit-base-patch16-384](https://huggingface.co/google/vit-base-patch16-384) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.5815
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- Precision: 0.8308
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- Recall: 0.9136
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- F1: 0.8703
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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: 2e-05
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- train_batch_size: 16
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- eval_batch_size: 16
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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: 5
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 |
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|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|
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| 0.081 | 1.0 | 327 | 0.3693 | 0.8464 | 0.8970 | 0.8710 |
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| 0.0151 | 2.0 | 654 | 0.4906 | 0.8171 | 0.8904 | 0.8521 |
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| 0.0066 | 3.0 | 981 | 0.5194 | 0.8416 | 0.9003 | 0.8700 |
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| 0.0029 | 4.0 | 1308 | 0.5671 | 0.8308 | 0.9136 | 0.8703 |
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| 0.0026 | 5.0 | 1635 | 0.5815 | 0.8308 | 0.9136 | 0.8703 |
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### Framework versions
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- Transformers 4.44.2
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- Pytorch 2.4.1+cu121
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- Datasets 3.0.0
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- Tokenizers 0.19.1
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