---
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: 0.4994
- Rewards/chosen: 0.0025
- Rewards/rejected: -0.0003
- Rewards/accuracies: 0.6038
- Rewards/margins: 0.0028
- Logps/rejected: -37.5434
- Logps/chosen: -33.7834
- Logits/rejected: -2.0909
- Logits/chosen: -2.0955

## 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: 4

### Training results

| Training Loss | Epoch | Step | Logits/chosen | Logits/rejected | Logps/chosen | Logps/rejected | Validation Loss | Rewards/accuracies | Rewards/chosen | Rewards/margins | Rewards/rejected |
|:-------------:|:-----:|:----:|:-------------:|:---------------:|:------------:|:--------------:|:---------------:|:------------------:|:--------------:|:---------------:|:----------------:|
| 0.4997        | 0.26  | 100  | -2.2320       | -2.2272         | -33.8530     | -37.3521       | 0.5000          | 0.5183             | 0.0018         | 0.0002          | 0.0016           |
| 0.4992        | 0.52  | 200  | -2.2288       | -2.2240         | -33.7422     | -37.2812       | 0.4999          | 0.5748             | 0.0029         | 0.0006          | 0.0024           |
| 0.4982        | 0.78  | 300  | -2.2289       | -2.2241         | -33.7545     | -37.2741       | 0.4999          | 0.5042             | 0.0028         | 0.0004          | 0.0024           |
| 0.4967        | 1.04  | 400  | 0.4999        | 0.0036          | 0.0030       | 0.5623         | 0.0006          | -37.2152           | -33.6722       | -2.2047         | -2.2095          |
| 0.4954        | 1.3   | 500  | 0.4998        | 0.0042          | 0.0033       | 0.5772         | 0.0009          | -37.1891           | -33.6191       | -2.1759         | -2.1807          |
| 0.4964        | 1.56  | 600  | 0.4996        | 0.0044          | 0.0026       | 0.5685         | 0.0018          | -37.2574           | -33.5925       | -2.1522         | -2.1569          |
| 0.4942        | 1.82  | 700  | 0.4996        | 0.0034          | 0.0018       | 0.5797         | 0.0016          | -37.3406           | -33.6981       | -2.1370         | -2.1417          |
| 0.4926        | 2.08  | 800  | 0.4995        | 0.0037          | 0.0013       | 0.5947         | 0.0024          | -37.3864           | -33.6678       | -2.1276         | -2.1323          |
| 0.491         | 2.34  | 900  | 0.4995        | 0.0031          | 0.0006       | 0.5739         | 0.0025          | -37.4562           | -33.7214       | -2.1107         | -2.1154          |
| 0.4941        | 2.6   | 1000 | 0.4995        | 0.0028          | 0.0001       | 0.6059         | 0.0027          | -37.5025           | -33.7503       | -2.0960         | -2.1006          |
| 0.4943        | 2.86  | 1100 | 0.4995        | 0.0025          | -0.0002      | 0.5826         | 0.0028          | -37.5382           | -33.7800       | -2.0918         | -2.0965          |
| 0.4911        | 3.12  | 1200 | 0.4995        | 0.0026          | -0.0001      | 0.6009         | 0.0027          | -37.5257           | -33.7754       | -2.0913         | -2.0959          |
| 0.4906        | 3.38  | 1300 | 0.4995        | 0.0025          | -0.0002      | 0.6034         | 0.0027          | -37.5366           | -33.7817       | -2.0909         | -2.0955          |
| 0.4928        | 3.64  | 1400 | 0.4995        | 0.0025          | -0.0003      | 0.5922         | 0.0028          | -37.5423           | -33.7843       | -2.0903         | -2.0950          |
| 0.4912        | 3.9   | 1500 | 0.4995        | 0.0025          | -0.0003      | 0.6034         | 0.0028          | -37.5427           | -33.7835       | -2.0908         | -2.0954          |


### Framework versions

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