--- 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: 0.4908 - Rewards/chosen: 0.0412 - Rewards/rejected: -0.0039 - Rewards/accuracies: 0.5868 - Rewards/margins: 0.0450 - Logps/rejected: -34.7175 - Logps/chosen: -31.0766 - Logits/rejected: -2.8191 - Logits/chosen: -2.8217 ## 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 | |:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:| | 0.4829 | 0.26 | 100 | 0.4945 | 0.0390 | 0.0134 | 0.5635 | 0.0256 | -34.6310 | -31.0874 | -2.8002 | -2.8030 | | 0.4376 | 0.52 | 200 | 0.4911 | 0.0473 | 0.0060 | 0.5577 | 0.0413 | -34.6682 | -31.0459 | -2.8137 | -2.8163 | | 0.4326 | 0.78 | 300 | 0.4909 | 0.0420 | -0.0034 | 0.6013 | 0.0454 | -34.7152 | -31.0725 | -2.8183 | -2.8209 | ### Framework versions - PEFT 0.10.0 - Transformers 4.39.0.dev0 - Pytorch 2.1.2+cu121 - Datasets 2.14.6 - Tokenizers 0.15.1