--- library_name: transformers license: other base_model: trl-lib/qwen1.5-0.5b-sft tags: - alignment-handbook - trl - simpo - generated_from_trainer - trl - simpo - generated_from_trainer datasets: - yakazimir/ultrafeedback_binarized model-index: - name: qwen_orpo_entropy_0_01 results: [] --- # qwen_orpo_entropy_0_01 This model is a fine-tuned version of [trl-lib/qwen1.5-0.5b-sft](https://huggingface.co/trl-lib/qwen1.5-0.5b-sft) on the yakazimir/ultrafeedback_binarized dataset. It achieves the following results on the evaluation set: - Loss: 0.5589 - Sft Loss: 3.3163 - Rewards/chosen: -3.1855 - Rewards/rejected: -4.1739 - Rewards/accuracies: 0.7226 - Rewards/margins: 0.9884 - Logps/rejected: -4.1739 - Logps/chosen: -3.1855 - Logits/rejected: 0.1645 - Logits/chosen: 0.0521 ## 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: 1e-06 - train_batch_size: 2 - eval_batch_size: 4 - seed: 42 - distributed_type: multi-GPU - gradient_accumulation_steps: 16 - total_train_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: 3.0 ### Training results | Training Loss | Epoch | Step | Validation Loss | Sft Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen | |:-------------:|:------:|:----:|:---------------:|:--------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:| | 0.7198 | 0.2141 | 400 | 0.7213 | 1.4421 | -1.5116 | -1.6721 | 0.5556 | 0.1605 | -1.6721 | -1.5116 | 0.3831 | 0.2918 | | 0.6256 | 0.4282 | 800 | 0.6211 | 2.0645 | -2.1064 | -2.5196 | 0.6654 | 0.4133 | -2.5196 | -2.1064 | 0.4328 | 0.3408 | | 0.6247 | 0.6422 | 1200 | 0.5880 | 2.6367 | -2.5144 | -3.0951 | 0.6966 | 0.5807 | -3.0951 | -2.5144 | 0.4051 | 0.3038 | | 0.5355 | 0.8563 | 1600 | 0.5751 | 2.5635 | -2.4305 | -2.9974 | 0.7062 | 0.5669 | -2.9974 | -2.4305 | 0.4192 | 0.3133 | | 0.6075 | 1.0704 | 2000 | 0.5675 | 2.6770 | -2.5347 | -3.1956 | 0.7166 | 0.6609 | -3.1956 | -2.5347 | 0.3536 | 0.2455 | | 0.5886 | 1.2845 | 2400 | 0.5600 | 2.9406 | -2.8008 | -3.5986 | 0.7292 | 0.7978 | -3.5986 | -2.8008 | 0.2408 | 0.1351 | | 0.5549 | 1.4986 | 2800 | 0.5573 | 2.8692 | -2.7229 | -3.5062 | 0.7248 | 0.7833 | -3.5062 | -2.7229 | 0.2546 | 0.1468 | | 0.5785 | 1.7127 | 3200 | 0.5549 | 2.8827 | -2.7303 | -3.5085 | 0.7240 | 0.7782 | -3.5085 | -2.7303 | 0.2599 | 0.1531 | | 0.5649 | 1.9267 | 3600 | 0.5509 | 2.9742 | -2.8066 | -3.6363 | 0.7240 | 0.8296 | -3.6363 | -2.8066 | 0.2062 | 0.0982 | | 0.4683 | 2.1408 | 4000 | 0.5601 | 3.3501 | -3.1588 | -4.1100 | 0.7196 | 0.9512 | -4.1100 | -3.1588 | 0.1350 | 0.0257 | | 0.491 | 2.3549 | 4400 | 0.5604 | 3.3569 | -3.2270 | -4.2111 | 0.7203 | 0.9841 | -4.2111 | -3.2270 | 0.2088 | 0.0922 | | 0.4967 | 2.5690 | 4800 | 0.5589 | 3.2861 | -3.1626 | -4.1414 | 0.7226 | 0.9787 | -4.1414 | -3.1626 | 0.1660 | 0.0539 | | 0.439 | 2.7831 | 5200 | 0.5584 | 3.3040 | -3.1772 | -4.1641 | 0.7211 | 0.9869 | -4.1641 | -3.1772 | 0.1462 | 0.0352 | | 0.4704 | 2.9972 | 5600 | 0.5590 | 3.3163 | -3.1855 | -4.1739 | 0.7226 | 0.9884 | -4.1739 | -3.1855 | 0.1645 | 0.0521 | ### Framework versions - Transformers 4.44.2 - Pytorch 2.2.2+cu121 - Datasets 2.18.0 - Tokenizers 0.19.1