--- library_name: peft tags: - trl - dpo - generated_from_trainer base_model: NorLLM-AI/NorMistral-7B model-index: - name: norllm-ai-normistral-7b-align-scan results: [] --- # norllm-ai-normistral-7b-align-scan This model is a fine-tuned version of [NorLLM-AI/NorMistral-7B](https://huggingface.co/NorLLM-AI/NorMistral-7B) on the None dataset. It achieves the following results on the evaluation set: - Loss: 23.8556 - Rewards/chosen: -0.0119 - Rewards/rejected: -0.0312 - Rewards/accuracies: 0.5718 - Rewards/margins: 0.0193 - Logps/rejected: -35.0104 - Logps/chosen: -31.4016 - Logits/rejected: -2.8159 - Logits/chosen: -2.8182 ## 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 | |:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:| | 22.8693 | 0.26 | 100 | 23.9885 | 0.0019 | -0.0147 | 0.6130 | 0.0166 | -34.8449 | -31.2633 | -2.8087 | -2.8112 | | 19.5946 | 0.52 | 200 | 23.7575 | -0.0117 | -0.0312 | 0.5718 | 0.0194 | -35.0097 | -31.3997 | -2.8172 | -2.8197 | | 18.7484 | 0.78 | 300 | 23.8556 | -0.0119 | -0.0312 | 0.5718 | 0.0193 | -35.0104 | -31.4016 | -2.8159 | -2.8182 | ### Framework versions - PEFT 0.10.0 - Transformers 4.39.0.dev0 - Pytorch 2.1.2+cu121 - Datasets 2.14.6 - Tokenizers 0.15.1