---
license: mit
library_name: peft
tags:
- trl
- reward-trainer
- generated_from_trainer
base_model: openai-community/gpt2-large
metrics:
- accuracy
model-index:
- name: RM-HH-Gemma_helpful_human_loraR64_20000_gpt2-large_shuffleTrue_extractchosenFalse
  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. -->

# RM-HH-Gemma_helpful_human_loraR64_20000_gpt2-large_shuffleTrue_extractchosenFalse

This model is a fine-tuned version of [openai-community/gpt2-large](https://huggingface.co/openai-community/gpt2-large) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6198
- Accuracy: 0.6546

## 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: 1
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2.0

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.703         | 0.06  | 250  | 0.7010          | 0.5414   |
| 0.6903        | 0.11  | 500  | 0.6820          | 0.5584   |
| 0.6715        | 0.17  | 750  | 0.6700          | 0.5805   |
| 0.6498        | 0.22  | 1000 | 0.6604          | 0.5985   |
| 0.6625        | 0.28  | 1250 | 0.6550          | 0.6070   |
| 0.6425        | 0.33  | 1500 | 0.6523          | 0.6170   |
| 0.6514        | 0.39  | 1750 | 0.6480          | 0.6226   |
| 0.6535        | 0.45  | 2000 | 0.6454          | 0.6256   |
| 0.6233        | 0.5   | 2250 | 0.6427          | 0.6296   |
| 0.6434        | 0.56  | 2500 | 0.6403          | 0.6306   |
| 0.6288        | 0.61  | 2750 | 0.6379          | 0.6421   |
| 0.632         | 0.67  | 3000 | 0.6360          | 0.6361   |
| 0.6365        | 0.72  | 3250 | 0.6337          | 0.6436   |
| 0.6329        | 0.78  | 3500 | 0.6322          | 0.6456   |
| 0.6278        | 0.84  | 3750 | 0.6312          | 0.6441   |
| 0.6369        | 0.89  | 4000 | 0.6299          | 0.6476   |
| 0.6313        | 0.95  | 4250 | 0.6292          | 0.6466   |
| 0.6315        | 1.0   | 4500 | 0.6285          | 0.6456   |
| 0.6039        | 1.06  | 4750 | 0.6278          | 0.6441   |
| 0.6259        | 1.11  | 5000 | 0.6268          | 0.6471   |
| 0.629         | 1.17  | 5250 | 0.6259          | 0.6481   |
| 0.6201        | 1.23  | 5500 | 0.6251          | 0.6506   |
| 0.6118        | 1.28  | 5750 | 0.6251          | 0.6521   |
| 0.6125        | 1.34  | 6000 | 0.6243          | 0.6481   |
| 0.6115        | 1.39  | 6250 | 0.6236          | 0.6476   |
| 0.6056        | 1.45  | 6500 | 0.6234          | 0.6506   |
| 0.6255        | 1.5   | 6750 | 0.6224          | 0.6501   |
| 0.6314        | 1.56  | 7000 | 0.6215          | 0.6511   |
| 0.6346        | 1.62  | 7250 | 0.6211          | 0.6501   |
| 0.6269        | 1.67  | 7500 | 0.6207          | 0.6516   |
| 0.6104        | 1.73  | 7750 | 0.6204          | 0.6526   |
| 0.6138        | 1.78  | 8000 | 0.6202          | 0.6526   |
| 0.6172        | 1.84  | 8250 | 0.6201          | 0.6541   |
| 0.6149        | 1.89  | 8500 | 0.6199          | 0.6541   |
| 0.6022        | 1.95  | 8750 | 0.6198          | 0.6546   |


### Framework versions

- PEFT 0.9.0
- Transformers 4.38.2
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.15.2