---
license: mit
base_model: openai-community/gpt2-large
tags:
- trl
- reward-trainer
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: RM-HH-AllMixNonPeft_harmless_gpt3_20000_gpt2-large_shuffleFalse_extractchosenTrue
  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-AllMixNonPeft_harmless_gpt3_20000_gpt2-large_shuffleFalse_extractchosenTrue

This model is a fine-tuned version of [openai-community/gpt2-large](https://huggingface.co/openai-community/gpt2-large) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0405
- Accuracy: 0.9850

## 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
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1.0

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.5457        | 0.17  | 250  | 0.0874          | 0.9654   |
| 0.5152        | 0.34  | 500  | 0.0660          | 0.9739   |
| 0.4916        | 0.51  | 750  | 0.0556          | 0.9804   |
| 0.4953        | 0.68  | 1000 | 0.0453          | 0.9827   |
| 0.4827        | 0.85  | 1250 | 0.0405          | 0.9850   |


### Framework versions

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