---
base_model: klue/roberta-large
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: reward-bert-duplicate-answer
  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. -->

# reward-bert-duplicate-answer

This model is a fine-tuned version of [klue/roberta-large](https://huggingface.co/klue/roberta-large) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0604
- Accuracy: 0.0

## 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: 9e-06
- train_batch_size: 4
- eval_batch_size: 4
- seed: 2023
- gradient_accumulation_steps: 8
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.95) and epsilon=1e-08
- lr_scheduler_type: cosine
- num_epochs: 1

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.2202        | 0.13  | 100  | 0.0750          | 0.0      |
| 0.1527        | 0.25  | 200  | 0.0377          | 0.0      |
| 0.1483        | 0.38  | 300  | 0.0729          | 0.0      |
| 0.1896        | 0.5   | 400  | 0.1465          | 0.0      |
| 0.1341        | 0.63  | 500  | 0.0729          | 0.0      |
| 0.0876        | 0.75  | 600  | 0.0351          | 0.0      |
| 0.1345        | 0.88  | 700  | 0.0604          | 0.0      |


### Framework versions

- Transformers 4.35.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1