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

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# RewardModelSmallerQuestionWithTwoLabels

This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co./bert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6213
- F1: 0.6909
- Roc Auc: 0.6913
- Accuracy: 0.6875

## 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: 2e-05
- 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: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     | Roc Auc | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:|
| No log        | 1.0   | 233  | 0.6765          | 0.5447 | 0.5675  | 0.5175   |
| No log        | 2.0   | 466  | 0.6107          | 0.6767 | 0.6775  | 0.665    |
| 0.6569        | 3.0   | 699  | 0.6213          | 0.6909 | 0.6913  | 0.6875   |
| 0.6569        | 4.0   | 932  | 0.9449          | 0.6683 | 0.6687  | 0.6675   |
| 0.3594        | 5.0   | 1165 | 1.0846          | 0.6816 | 0.6812  | 0.6775   |


### Framework versions

- Transformers 4.32.1
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3