--- license: apache-2.0 library_name: peft tags: - trl - dpo - generated_from_trainer base_model: openbmb/Eurus-7b-sft model-index: - name: eurus-7b-cost-UI-5e-7 results: [] --- # eurus-7b-cost-UI-5e-7 This model is a fine-tuned version of [openbmb/Eurus-7b-sft](https://huggingface.co/openbmb/Eurus-7b-sft) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.6940 - Rewards/chosen: -0.7885 - Rewards/rejected: -0.8474 - Rewards/accuracies: 0.5380 - Rewards/margins: 0.0589 - Rewards/margins Max: 0.7289 - Rewards/margins Min: -0.5646 - Rewards/margins Std: 0.4226 - Logps/rejected: -347.4267 - Logps/chosen: -352.6256 - Logits/rejected: -2.1189 - Logits/chosen: -2.2153 ## 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-07 - train_batch_size: 2 - eval_batch_size: 8 - seed: 42 - distributed_type: multi-GPU - num_devices: 2 - gradient_accumulation_steps: 4 - total_train_batch_size: 16 - total_eval_batch_size: 16 - 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 | Rewards/margins Max | Rewards/margins Min | Rewards/margins Std | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen | |:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:-------------------:|:-------------------:|:-------------------:|:--------------:|:------------:|:---------------:|:-------------:| | 0.1653 | 1.0 | 1648 | 0.6940 | -0.7885 | -0.8474 | 0.5380 | 0.0589 | 0.7289 | -0.5646 | 0.4226 | -347.4267 | -352.6256 | -2.1189 | -2.2153 | ### Framework versions - PEFT 0.7.1 - Transformers 4.39.0.dev0 - Pytorch 2.1.2+cu121 - Datasets 2.14.6 - Tokenizers 0.15.2