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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: 2.7902
- Rewards/chosen: -0.0060
- Rewards/rejected: -0.0171
- Rewards/accuracies: 0.5602
- Rewards/margins: 0.0111
- Logps/rejected: -37.5735
- Logps/chosen: -34.0545
- Logits/rejected: -2.2247
- Logits/chosen: -2.2295
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 2.59 | 0.26 | 100 | 2.8958 | 0.0029 | 0.0052 | 0.4730 | -0.0024 | -37.4993 | -34.0250 | -2.2305 | -2.2353 |
| 2.2795 | 0.52 | 200 | 2.8012 | -0.0060 | -0.0145 | 0.5278 | 0.0085 | -37.5651 | -34.0545 | -2.2290 | -2.2339 |
| 1.7902 | 0.78 | 300 | 2.7585 | -0.0030 | -0.0167 | 0.5748 | 0.0137 | -37.5724 | -34.0446 | -2.2245 | -2.2294 |
### Framework versions
- PEFT 0.8.2
- Transformers 4.37.2
- Pytorch 2.1.2+cu121
- Datasets 2.17.0
- Tokenizers 0.15.1 |