--- library_name: peft tags: - trl - dpo - generated_from_trainer base_model: allenai/tulu-2-13b model-index: - name: tulu2-13b-cost-UF-5e-7-nojudge results: [] --- # tulu2-13b-cost-UF-5e-7-nojudge This model is a fine-tuned version of [allenai/tulu-2-13b](https://huggingface.co/allenai/tulu-2-13b) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.6931 - Rewards/chosen: 0.0268 - Rewards/rejected: 0.0260 - Rewards/accuracies: 0.5450 - Rewards/margins: 0.0008 - Rewards/margins Max: 0.0629 - Rewards/margins Min: -0.0642 - Rewards/margins Std: 0.0421 - Logps/rejected: -327.6042 - Logps/chosen: -331.2294 - Logits/rejected: -0.8979 - Logits/chosen: -1.0239 ## 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: 4 - gradient_accumulation_steps: 2 - total_train_batch_size: 16 - total_eval_batch_size: 32 - 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 | |:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:-------------------:|:-------------------:|:-------------------:|:--------------:|:------------:|:---------------:|:-------------:| | 0.6681 | 1.0 | 1245 | 0.6931 | 0.0268 | 0.0260 | 0.5450 | 0.0008 | 0.0629 | -0.0642 | 0.0421 | -327.6042 | -331.2294 | -0.8979 | -1.0239 | ### Framework versions - PEFT 0.7.1 - Transformers 4.39.0.dev0 - Pytorch 2.1.2+cu121 - Datasets 2.14.6 - Tokenizers 0.15.2