--- library_name: peft tags: - trl - dpo - generated_from_trainer base_model: allenai/tulu-2-7b model-index: - name: tulu2-7b-cost-UF-UI-judge13b-5e-7 results: [] --- # tulu2-7b-cost-UF-UI-judge13b-5e-7 This model is a fine-tuned version of [allenai/tulu-2-7b](https://huggingface.co/allenai/tulu-2-7b) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.6929 - Rewards/chosen: 0.0029 - Rewards/rejected: 0.0023 - Rewards/accuracies: 0.5365 - Rewards/margins: 0.0006 - Rewards/margins Max: 0.0723 - Rewards/margins Min: -0.0823 - Rewards/margins Std: 0.0504 - Logps/rejected: -318.0156 - Logps/chosen: -337.8507 - Logits/rejected: 0.8998 - Logits/chosen: 0.7298 ## 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 | |:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:-------------------:|:-------------------:|:-------------------:|:--------------:|:------------:|:---------------:|:-------------:| | 0.6604 | 1.0 | 1724 | 0.6929 | 0.0029 | 0.0023 | 0.5365 | 0.0006 | 0.0723 | -0.0823 | 0.0504 | -318.0156 | -337.8507 | 0.8998 | 0.7298 | ### Framework versions - PEFT 0.7.1 - Transformers 4.39.0.dev0 - Pytorch 2.1.2+cu121 - Datasets 2.14.6 - Tokenizers 0.15.2