--- 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: [] --- # 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: 0.9658 - Rewards/chosen: -0.0301 - Rewards/rejected: -0.0652 - Rewards/accuracies: 0.5278 - Rewards/margins: 0.0352 - Logps/rejected: -37.6098 - Logps/chosen: -34.0775 - Logits/rejected: -2.2182 - Logits/chosen: -2.2231 ## 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 | |:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:| | 0.8961 | 0.26 | 100 | 0.9767 | 0.0065 | -0.0170 | 0.5365 | 0.0235 | -37.5409 | -34.0252 | -2.2266 | -2.2315 | | 0.7699 | 0.52 | 200 | 0.9742 | -0.0141 | -0.0400 | 0.5303 | 0.0259 | -37.5737 | -34.0547 | -2.2234 | -2.2282 | | 0.6723 | 0.78 | 300 | 0.9761 | -0.0366 | -0.0616 | 0.5299 | 0.0250 | -37.6047 | -34.0868 | -2.2186 | -2.2234 | ### Framework versions - PEFT 0.8.2 - Transformers 4.37.2 - Pytorch 2.1.2+cu121 - Datasets 2.17.0 - Tokenizers 0.15.1