---
library_name: peft
tags:
- alignment-handbook
- trl
- dpo
- generated_from_trainer
base_model: NbAiLab/nb-gpt-j-6B-v2
datasets:
- hugodk-sch/aftonposten_title_prefs
model-index:
- name: aftonposten-6b-align-scan
  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. -->

# aftonposten-6b-align-scan

This model is a fine-tuned version of [data/ap-gpt-j-6b-sft-qlora-04-08](https://huggingface.co/data/ap-gpt-j-6b-sft-qlora-04-08) on the hugodk-sch/aftonposten_title_prefs dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4934
- Rewards/chosen: 0.2139
- Rewards/rejected: 0.1872
- Rewards/accuracies: 0.5457
- Rewards/margins: 0.0267
- Logps/rejected: -37.2826
- Logps/chosen: -33.7672
- Logits/rejected: -2.2262
- Logits/chosen: -2.2310

## 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: 5e-06
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 1

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.4749        | 0.26  | 100  | 0.4963          | 0.1467         | 0.1303           | 0.5336             | 0.0164          | -37.3537       | -33.8512     | -2.2327         | -2.2375       |
| 0.4376        | 0.52  | 200  | 0.4956          | 0.1959         | 0.1769           | 0.5486             | 0.0191          | -37.2955       | -33.7896     | -2.2291         | -2.2339       |
| 0.3835        | 0.78  | 300  | 0.4950          | 0.2045         | 0.1836           | 0.5245             | 0.0210          | -37.2872       | -33.7789     | -2.2264         | -2.2312       |


### Framework versions

- PEFT 0.8.2
- Transformers 4.37.2
- Pytorch 2.1.2+cu121
- Datasets 2.17.0
- Tokenizers 0.15.1