--- license: mit library_name: peft tags: - alignment-handbook - generated_from_trainer - trl - dpo - generated_from_trainer datasets: - HuggingFaceH4/ultrafeedback_binarized base_model: microsoft/phi-2 model-index: - name: phi-2-gpo-ultrachat-lora-2 results: [] --- # phi-2-gpo-ultrachat-lora-2 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: 0.0093 - Rewards/chosen: -0.0154 - Rewards/rejected: -0.0218 - Rewards/accuracies: 0.3500 - Rewards/margins: 0.0064 - Logps/rejected: -96.3794 - Logps/chosen: -93.2678 - Logits/rejected: 0.7520 - Logits/chosen: 0.7332 ## 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 - num_devices: 4 - gradient_accumulation_steps: 4 - total_train_batch_size: 64 - 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: 2 ### Training results | Training Loss | Epoch | Step | Logits/chosen | Logits/rejected | Logps/chosen | Logps/rejected | Validation Loss | Rewards/accuracies | Rewards/chosen | Rewards/margins | Rewards/rejected | |:-------------:|:-----:|:----:|:-------------:|:---------------:|:------------:|:--------------:|:---------------:|:------------------:|:--------------:|:---------------:|:----------------:| | 0.01 | 1.04 | 100 | 0.8011 | 0.8188 | -91.7671 | -94.2623 | 0.0100 | 0.25 | -0.0004 | 0.0003 | -0.0007 | | 0.0098 | 0.42 | 200 | 0.0098 | -0.0018 | -0.0032 | 0.3060 | 0.0015 | -94.5191 | -91.9032 | 0.8107 | 0.7928 | | 0.0095 | 0.63 | 300 | 0.0096 | -0.0058 | -0.0088 | 0.3060 | 0.0030 | -95.0819 | -92.3092 | 0.7982 | 0.7800 | | 0.0091 | 0.84 | 400 | 0.0094 | -0.0110 | -0.0157 | 0.3340 | 0.0047 | -95.7642 | -92.8250 | 0.7753 | 0.7565 | | 0.0094 | 1.05 | 500 | 0.0093 | -0.0132 | -0.0192 | 0.3400 | 0.0060 | -96.1150 | -93.0463 | 0.7679 | 0.7492 | | 0.0093 | 1.26 | 600 | 0.0093 | -0.0144 | -0.0207 | 0.3440 | 0.0063 | -96.2631 | -93.1677 | 0.7578 | 0.7383 | | 0.009 | 1.47 | 700 | 0.0093 | -0.0152 | -0.0212 | 0.3480 | 0.0060 | -96.3198 | -93.2491 | 0.7545 | 0.7355 | | 0.009 | 1.67 | 800 | 0.0093 | -0.0155 | -0.0218 | 0.3420 | 0.0063 | -96.3791 | -93.2749 | 0.7523 | 0.7328 | | 0.0091 | 1.88 | 900 | 0.0093 | -0.0156 | -0.0218 | 0.3480 | 0.0063 | -96.3809 | -93.2841 | 0.7515 | 0.7320 | ### Framework versions - PEFT 0.7.1 - Transformers 4.36.2 - Pytorch 2.1.2+cu118 - Datasets 2.14.6 - Tokenizers 0.15.2