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---
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: 0.4913
- Rewards/chosen: 0.1914
- Rewards/rejected: 0.1556
- Rewards/accuracies: 0.5453
- Rewards/margins: 0.0358
- Logps/rejected: -37.2944
- Logps/chosen: -33.7611
- Logits/rejected: -2.2272
- Logits/chosen: -2.2320
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.4799 | 0.26 | 100 | 0.4978 | 0.1217 | 0.1117 | 0.5341 | 0.0100 | -37.3570 | -33.8607 | -2.2333 | -2.2381 |
| 0.4453 | 0.52 | 200 | 0.4928 | 0.1862 | 0.1561 | 0.5370 | 0.0302 | -37.2937 | -33.7685 | -2.2299 | -2.2347 |
| 0.3947 | 0.78 | 300 | 0.4910 | 0.1956 | 0.1591 | 0.5565 | 0.0365 | -37.2894 | -33.7551 | -2.2274 | -2.2322 |
### Framework versions
- PEFT 0.8.2
- Transformers 4.37.2
- Pytorch 2.1.2+cu121
- Datasets 2.17.0
- Tokenizers 0.15.1 |