--- library_name: peft tags: - alignment-handbook - trl - dpo - generated_from_trainer base_model: NorLLM-AI/NorMistral-7B datasets: - hugodk-sch/aftonposten_title_prefs model-index: - name: norllm-ai-normistral-7b-align-scan results: [] --- # norllm-ai-normistral-7b-align-scan This model is a fine-tuned version of [data/norllm-ai-normistral-7b-sft-qlora](https://huggingface.co/data/norllm-ai-normistral-7b-sft-qlora) on the hugodk-sch/aftonposten_title_prefs dataset. It achieves the following results on the evaluation set: - Loss: 0.6726 - Rewards/chosen: -0.0859 - Rewards/rejected: -0.1885 - Rewards/accuracies: 0.5627 - Rewards/margins: 0.1027 - Logps/rejected: -35.0124 - Logps/chosen: -31.4256 - Logits/rejected: -2.8174 - Logits/chosen: -2.8199 ## 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 | |:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:| | 0.6371 | 0.26 | 100 | 0.6738 | 0.0094 | -0.0765 | 0.6013 | 0.0860 | -34.8257 | -31.2667 | -2.8093 | -2.8120 | | 0.5701 | 0.52 | 200 | 0.6704 | -0.0753 | -0.1790 | 0.5777 | 0.1037 | -34.9964 | -31.4080 | -2.8197 | -2.8224 | | 0.5462 | 0.78 | 300 | 0.6756 | -0.0773 | -0.1729 | 0.5569 | 0.0956 | -34.9863 | -31.4113 | -2.8175 | -2.8199 | ### Framework versions - PEFT 0.10.0 - Transformers 4.39.0.dev0 - Pytorch 2.1.2+cu121 - Datasets 2.14.6 - Tokenizers 0.15.1