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---
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
metrics:
- f1
- accuracy
model-index:
- name: RewardModel_TwoLabels_OnlyOnAnswer
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. -->
# RewardModel_TwoLabels_OnlyOnAnswer
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: 0.7137
- F1: 0.735
- Roc Auc: 0.7350
- Accuracy: 0.735
## 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 | 258 | 0.6715 | 0.5441 | 0.5475 | 0.54 |
| 0.6118 | 2.0 | 516 | 0.6098 | 0.7 | 0.7 | 0.695 |
| 0.6118 | 3.0 | 774 | 0.7137 | 0.735 | 0.7350 | 0.735 |
| 0.295 | 4.0 | 1032 | 1.1055 | 0.685 | 0.685 | 0.685 |
| 0.295 | 5.0 | 1290 | 1.2907 | 0.69 | 0.69 | 0.69 |
### Framework versions
- Transformers 4.32.1
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3
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