---
license: apache-2.0
library_name: peft
tags:
- generated_from_trainer
metrics:
- accuracy
base_model: EleutherAI/gpt-j-6b
model-index:
- name: trl_rm_tldr_gptj
  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. -->

# trl_rm_tldr_gptj

This model is a fine-tuned version of [EleutherAI/gpt-j-6b](https://huggingface.co./EleutherAI/gpt-j-6b) on the TL;DR dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6624
- Accuracy: 0.6857

## 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: 1.41e-05
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.5633        | 1.0   | 22660 | 0.6624          | 0.6857   |


### Framework versions

- PEFT 0.7.1.dev0
- Transformers 4.36.2
- Pytorch 2.1.2
- Datasets 2.15.0
- Tokenizers 0.15.0

### BibTex Citation
If you would like to cite our paper when using the model, please use
```
@article{sun2024supervised,
  title={Supervised Fine-Tuning as Inverse Reinforcement Learning},
  author={Sun, Hao},
  journal={arXiv preprint arXiv:2403.12017},
  year={2024}
}
```