--- license: mit library_name: peft tags: - alignment-handbook - generated_from_trainer - trl - dpo - generated_from_trainer base_model: microsoft/phi-2 datasets: - HuggingFaceH4/ultrafeedback_binarized model-index: - name: phi-2-gpo-test-longest-iter-0 results: [] --- # phi-2-gpo-test-longest-iter-0 This model is a fine-tuned version of [lole25/phi-2-sft-ultrachat-lora](https://huggingface.co/lole25/phi-2-sft-ultrachat-lora) on the HuggingFaceH4/ultrafeedback_binarized dataset. It achieves the following results on the evaluation set: - Loss: 0.0103 - Rewards/chosen: 0.0007 - Rewards/rejected: 0.0005 - Rewards/accuracies: 0.5035 - Rewards/margins: 0.0001 - Logps/rejected: -233.4872 - Logps/chosen: -256.5486 - Logits/rejected: 0.8934 - Logits/chosen: 0.8359 ## 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: 4 - seed: 42 - distributed_type: multi-GPU - gradient_accumulation_steps: 4 - total_train_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: 2 ### Training results | Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen | |:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:| | 0.0101 | 1.6 | 100 | 0.0102 | 0.0004 | 0.0001 | 0.5020 | 0.0003 | -233.5265 | -256.5746 | 0.8922 | 0.8348 | ### Framework versions - PEFT 0.7.1 - Transformers 4.36.2 - Pytorch 2.2.1+cu121 - Datasets 2.14.6 - Tokenizers 0.15.2