--- 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: 1.6120 - Rewards/chosen: 0.0138 - Rewards/rejected: -0.0163 - Rewards/accuracies: 0.5689 - Rewards/margins: 0.0302 - Logps/rejected: -34.7390 - Logps/chosen: -31.2479 - Logits/rejected: -2.8036 - Logits/chosen: -2.8061 ## 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 | |:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:| | 1.7948 | 0.26 | 100 | 1.6241 | 0.0102 | -0.0177 | 0.5685 | 0.0278 | -34.7424 | -31.2571 | -2.8147 | -2.8176 | | 2.6629 | 0.52 | 200 | 1.5649 | 0.0182 | -0.0143 | 0.5457 | 0.0325 | -34.7338 | -31.2369 | -2.8095 | -2.8121 | | 1.5067 | 0.78 | 300 | 1.6904 | 0.0126 | -0.0056 | 0.5573 | 0.0181 | -34.7121 | -31.2510 | -2.8041 | -2.8065 | ### Framework versions - PEFT 0.10.0 - Transformers 4.39.0.dev0 - Pytorch 2.1.2+cu121 - Datasets 2.14.6 - Tokenizers 0.15.1