--- 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: 0.7391 - Rewards/chosen: -0.0991 - Rewards/rejected: -0.2198 - Rewards/accuracies: 0.5486 - Rewards/margins: 0.1207 - Logps/rejected: -36.2805 - Logps/chosen: -32.5848 - Logits/rejected: 98.6399 - Logits/chosen: 98.6637 ## 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 | |:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:| | 0.6331 | 0.26 | 100 | 0.7266 | 0.0018 | -0.0892 | 0.5453 | 0.0910 | -36.0939 | -32.4406 | 98.7381 | 98.7510 | | 0.6048 | 0.52 | 200 | 0.7483 | -0.1575 | -0.2719 | 0.5282 | 0.1144 | -36.3550 | -32.6682 | 98.6127 | 98.6356 | | 0.5829 | 0.78 | 300 | 0.7391 | -0.0991 | -0.2198 | 0.5486 | 0.1207 | -36.2805 | -32.5848 | 98.6399 | 98.6637 | ### Framework versions - PEFT 0.10.0 - Transformers 4.39.0.dev0 - Pytorch 2.1.2+cu121 - Datasets 2.14.6 - Tokenizers 0.15.1