---
library_name: transformers
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
metrics:
- f1
- accuracy
model-index:
- name: OR_finetuned_classification
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# OR_finetuned_classification

This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6007
- F1: 0.6667
- Roc Auc: 0.8095
- Accuracy: 0.6667

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 0.0002
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 300

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     | Roc Auc | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:|
| 0.0016        | 79.0  | 790  | 0.4859          | 0.6667 | 0.8095  | 0.6667   |
| 0.0006        | 158.0 | 1580 | 0.5649          | 0.6667 | 0.8095  | 0.6667   |
| 0.0004        | 237.0 | 2370 | 0.6007          | 0.6667 | 0.8095  | 0.6667   |


### Framework versions

- Transformers 4.45.2
- Pytorch 2.4.0+cu124
- Datasets 3.0.1
- Tokenizers 0.20.1