---
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: 0.4730
- Rewards/chosen: 0.2464
- Rewards/rejected: 0.1175
- Rewards/accuracies: 0.5947
- Rewards/margins: 0.1288
- Logps/rejected: -37.3207
- Logps/chosen: -33.6239
- Logits/rejected: -2.1470
- Logits/chosen: -2.1517

## 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 |
|:-------------:|:-----:|:----:|:-------------:|:---------------:|:------------:|:--------------:|:---------------:|:------------------:|:--------------:|:---------------:|:----------------:|
| 0.4799        | 0.26  | 100  | -2.2349       | -2.2301         | -33.9029     | -37.3943       | 0.4987          | 0.5104             | 0.0790         | 0.0056          | 0.0734           |
| 0.4548        | 0.52  | 200  | -2.2335       | -2.2287         | -33.7696     | -37.2846       | 0.4956          | 0.5341             | 0.1590         | 0.0198          | 0.1392           |
| 0.41          | 0.78  | 300  | -2.2309       | -2.2261         | -33.7614     | -37.2848       | 0.4937          | 0.5361             | 0.1639         | 0.0248          | 0.1391           |
| 0.3497        | 1.04  | 400  | 0.4927        | 0.2171          | 0.1863       | 0.5652         | 0.0309          | -37.2062           | -33.6727       | -2.2113         | -2.2162          |
| 0.2906        | 1.3   | 500  | 0.4870        | 0.2484          | 0.1921       | 0.5922         | 0.0563          | -37.1964           | -33.6205       | -2.1834         | -2.1881          |
| 0.3014        | 1.56  | 600  | 0.4796        | 0.2630          | 0.1719       | 0.5797         | 0.0911          | -37.2301           | -33.5962       | -2.1694         | -2.1741          |
| 0.2776        | 1.82  | 700  | 0.4825        | 0.2341          | 0.1554       | 0.5768         | 0.0787          | -37.2576           | -33.6444       | -2.1625         | -2.1672          |
| 0.201         | 2.08  | 800  | 0.4766        | 0.2639          | 0.1595       | 0.5914         | 0.1043          | -37.2507           | -33.5948       | -2.1641         | -2.1689          |
| 0.1721        | 2.34  | 900  | 0.4749        | 0.2446          | 0.1298       | 0.5860         | 0.1148          | -37.3003           | -33.6269       | -2.1516         | -2.1563          |
| 0.2259        | 2.6   | 1000 | 0.4736        | 0.2483          | 0.1257       | 0.5860         | 0.1226          | -37.3072           | -33.6207       | -2.1481         | -2.1528          |
| 0.2405        | 2.86  | 1100 | 0.4740        | 0.2438          | 0.1229       | 0.5860         | 0.1209          | -37.3118           | -33.6283       | -2.1475         | -2.1522          |
| 0.1793        | 3.12  | 1200 | 0.4746        | 0.2441          | 0.1249       | 0.5685         | 0.1192          | -37.3085           | -33.6277       | -2.1469         | -2.1516          |
| 0.1633        | 3.38  | 1300 | 0.4744        | 0.2433          | 0.1235       | 0.6009         | 0.1198          | -37.3107           | -33.6290       | -2.1471         | -2.1518          |
| 0.202         | 3.64  | 1400 | 0.4748        | 0.2450          | 0.1279       | 0.5831         | 0.1170          | -37.3034           | -33.6263       | -2.1472         | -2.1519          |
| 0.1889        | 3.9   | 1500 | 0.4727        | 0.2480          | 0.1188       | 0.6005         | 0.1292          | -37.3186           | -33.6212       | -2.1470         | -2.1517          |


### Framework versions

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