--- 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: 0.4970 - Rewards/chosen: 0.0579 - Rewards/rejected: 0.0502 - Rewards/accuracies: 0.5565 - Rewards/margins: 0.0077 - Logps/rejected: -35.8660 - Logps/chosen: -32.3273 - Logits/rejected: 98.3156 - Logits/chosen: 98.3222 ## 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 | |:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:| | 0.4665 | 0.26 | 100 | 0.4971 | 0.0771 | 0.0651 | 0.5187 | 0.0119 | -35.8363 | -32.2890 | 98.7124 | 98.7206 | | 0.3678 | 0.52 | 200 | 0.4983 | -0.0042 | -0.0160 | 0.5104 | 0.0118 | -35.9986 | -32.4516 | 98.3577 | 98.3655 | | 0.3546 | 0.78 | 300 | 0.4970 | 0.0579 | 0.0502 | 0.5565 | 0.0077 | -35.8660 | -32.3273 | 98.3156 | 98.3222 | ### Framework versions - PEFT 0.10.0 - Transformers 4.39.0.dev0 - Pytorch 2.1.2+cu121 - Datasets 2.14.6 - Tokenizers 0.15.1