---
license: mit
base_model: mNLP-project/gpt2-finetuned
tags:
- trl
- dpo
- generated_from_trainer
model-index:
- name: gpt2-dpo
  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. -->

# gpt2-dpo

This model is a fine-tuned version of [mNLP-project/gpt2-finetuned](https://huggingface.co/mNLP-project/gpt2-finetuned) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6350
- Rewards/chosen: 1.6222
- Rewards/rejected: 1.3204
- Rewards/accuracies: 0.6496
- Rewards/margins: 0.3018
- Logps/rejected: -780.0735
- Logps/chosen: -933.2262
- Logits/rejected: -34.5449
- Logits/chosen: -28.7838

## 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-06
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.2
- num_epochs: 10

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.6286        | 0.9993 | 668  | 0.6350          | 1.6222         | 1.3204           | 0.6496             | 0.3018          | -780.0735      | -933.2262    | -34.5449        | -28.7838      |
| 0.6387        | 2.0    | 1337 | 0.6662          | 1.8546         | 1.5416           | 0.6302             | 0.3130          | -777.8622      | -930.9024    | -34.5110        | -28.7424      |
| 0.5643        | 2.9993 | 2005 | 0.6635          | 2.0534         | 1.6918           | 0.6396             | 0.3616          | -776.3599      | -928.9147    | -34.5066        | -28.7168      |
| 0.4487        | 4.0    | 2674 | 0.6677          | 2.2748         | 1.8809           | 0.6451             | 0.3940          | -774.4694      | -926.7002    | -34.1409        | -28.2530      |
| 0.3831        | 4.9993 | 3342 | 0.6783          | 2.4765         | 2.0527           | 0.6418             | 0.4238          | -772.7513      | -924.6838    | -34.0051        | -28.0668      |
| 0.352         | 6.0    | 4011 | 0.6782          | 2.4441         | 2.0097           | 0.6440             | 0.4344          | -773.1808      | -925.0074    | -34.0868        | -28.1418      |
| 0.3189        | 6.9993 | 4679 | 0.6840          | 2.2310         | 1.8303           | 0.6343             | 0.4008          | -774.9752      | -927.1384    | -33.9525        | -27.9466      |
| 0.3006        | 8.0    | 5348 | 0.6882          | 2.4339         | 1.9918           | 0.6388             | 0.4422          | -773.3604      | -925.1093    | -33.7716        | -27.7551      |
| 0.3152        | 8.9993 | 6016 | 0.6891          | 2.4920         | 2.0457           | 0.6407             | 0.4462          | -772.8206      | -924.5289    | -33.6753        | -27.6463      |
| 0.2752        | 9.9925 | 6680 | 0.6892          | 2.4562         | 2.0151           | 0.6410             | 0.4411          | -773.1274      | -924.8871    | -33.6818        | -27.6538      |


### Framework versions

- Transformers 4.40.2
- Pytorch 2.1.0+cu118
- Datasets 2.19.1
- Tokenizers 0.19.1