--- license: apache-2.0 library_name: peft tags: - trl - dpo - generated_from_trainer base_model: norallm/normistral-7b-warm model-index: - name: ap-normistral-7b-align-scan results: [] --- # ap-normistral-7b-align-scan This model is a fine-tuned version of [norallm/normistral-7b-warm](https://huggingface.co/norallm/normistral-7b-warm) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.4855 - Rewards/chosen: 0.1659 - Rewards/rejected: 0.0986 - Rewards/accuracies: 0.5282 - Rewards/margins: 0.0673 - Logps/rejected: -35.8433 - Logps/chosen: -32.2358 - Logits/rejected: 98.4267 - Logits/chosen: 98.4293 ## 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 | |:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:| | 0.4705 | 0.26 | 100 | 0.4947 | 0.1342 | 0.1226 | 0.4896 | 0.0116 | -35.8133 | -32.2754 | 98.6750 | 98.6871 | | 0.3097 | 0.52 | 200 | 0.4910 | 0.1604 | 0.1008 | 0.5482 | 0.0596 | -35.8405 | -32.2427 | 98.4702 | 98.4771 | | 0.3066 | 0.78 | 300 | 0.4855 | 0.1659 | 0.0986 | 0.5282 | 0.0673 | -35.8433 | -32.2358 | 98.4267 | 98.4293 | ### Framework versions - PEFT 0.10.0 - Transformers 4.39.0.dev0 - Pytorch 2.1.2+cu121 - Datasets 2.14.6 - Tokenizers 0.15.1