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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: bert-base-uncased
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tags:
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- generated_from_trainer
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metrics:
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- f1
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- accuracy
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model-index:
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- name: OR_finetuned_classification
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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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# OR_finetuned_classification
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This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.6007
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- F1: 0.6667
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- Roc Auc: 0.8095
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- Accuracy: 0.6667
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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: 8
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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: 300
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | F1 | Roc Auc | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:|
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| 0.0016 | 79.0 | 790 | 0.4859 | 0.6667 | 0.8095 | 0.6667 |
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| 0.0006 | 158.0 | 1580 | 0.5649 | 0.6667 | 0.8095 | 0.6667 |
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| 0.0004 | 237.0 | 2370 | 0.6007 | 0.6667 | 0.8095 | 0.6667 |
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### Framework versions
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- Transformers 4.45.2
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- Pytorch 2.4.0+cu124
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- Datasets 3.0.1
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- Tokenizers 0.20.1
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