---
license: mit
base_model: EleutherAI/gpt-neo-125m
tags:
- trl
- dpo
- generated_from_trainer
model-index:
- name: gpt-neo-125m_hh_reward
  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. -->

# gpt-neo-125m_hh_reward

This model is a fine-tuned version of [EleutherAI/gpt-neo-125m](https://huggingface.co/EleutherAI/gpt-neo-125m) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7764
- Rewards/chosen: -1.0726
- Rewards/rejected: -1.1588
- Rewards/accuracies: 0.5592
- Rewards/margins: 0.0861
- Logps/rejected: -127.6699
- Logps/chosen: -107.5507
- Logits/rejected: -15.9221
- Logits/chosen: -15.7406

## 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: 1e-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
- lr_scheduler_warmup_steps: 150
- training_steps: 20050

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
|:-------------:|:-----:|:-----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.7685        | 0.1   | 2000  | 0.7585          | -0.6757        | -0.7643          | 0.5066             | 0.0886          | -126.6837      | -106.5583    | -16.3107        | -16.1234      |
| 0.795         | 0.2   | 4000  | 0.7531          | -0.9330        | -1.0793          | 0.5625             | 0.1463          | -127.4711      | -107.2016    | -16.6020        | -16.4468      |
| 0.7366        | 0.3   | 6000  | 0.7961          | -1.0751        | -1.1163          | 0.5033             | 0.0412          | -127.5638      | -107.5568    | -16.3735        | -16.2226      |
| 0.8288        | 0.4   | 8000  | 0.7860          | -1.0546        | -1.1457          | 0.5559             | 0.0911          | -127.6372      | -107.5056    | -16.4345        | -16.2588      |
| 0.7272        | 0.5   | 10000 | 0.7767          | -1.1017        | -1.2133          | 0.5658             | 0.1116          | -127.8062      | -107.6233    | -16.2325        | -16.0800      |
| 0.8404        | 0.6   | 12000 | 0.8029          | -1.2133        | -1.2948          | 0.5329             | 0.0815          | -128.0099      | -107.9024    | -15.9207        | -15.7572      |
| 0.8224        | 0.7   | 14000 | 0.7702          | -1.0578        | -1.1817          | 0.5625             | 0.1239          | -127.7272      | -107.5137    | -15.9578        | -15.7879      |
| 0.7267        | 0.8   | 16000 | 0.7929          | -1.1534        | -1.2255          | 0.5559             | 0.0721          | -127.8368      | -107.7526    | -16.0551        | -15.8740      |
| 0.6329        | 0.9   | 18000 | 0.8052          | -1.0222        | -1.0692          | 0.5428             | 0.0471          | -127.4461      | -107.4246    | -15.8842        | -15.7008      |
| 0.7247        | 1.0   | 20000 | 0.7764          | -1.0726        | -1.1588          | 0.5592             | 0.0861          | -127.6699      | -107.5507    | -15.9221        | -15.7406      |


### Framework versions

- Transformers 4.36.2
- Pytorch 2.0.1+cu117
- Datasets 2.14.5
- Tokenizers 0.15.0