--- library_name: transformers base_model: jackf857/qwen3-8b-base-sft-ultrachat-4xh200-batch-128 tags: - alignment-handbook - orpo - generated_from_trainer datasets: - HuggingFaceH4/ultrafeedback_binarized model-index: - name: qwen3-8b-base-orpo-ultrafeedback-4xh200-batch-128 results: [] --- # qwen3-8b-base-orpo-ultrafeedback-4xh200-batch-128 This model is a fine-tuned version of [jackf857/qwen3-8b-base-sft-ultrachat-4xh200-batch-128](https://huggingface.co/jackf857/qwen3-8b-base-sft-ultrachat-4xh200-batch-128) on the HuggingFaceH4/ultrafeedback_binarized dataset. It achieves the following results on the evaluation set: - Loss: 1.0784 - Rewards/chosen: -0.0085 - Rewards/rejected: -0.0105 - Rewards/accuracies: 0.6060 - Rewards/margins: 0.0020 - Logps/rejected: -1.0496 - Logps/chosen: -0.8523 - Logits/rejected: 2.1915 - Logits/chosen: 2.1569 - Nll Loss: 1.1100 - Log Odds Ratio: -0.6630 - Log Odds Chosen: 0.3031 ## 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: 4 - eval_batch_size: 2 - seed: 42 - distributed_type: multi-GPU - num_devices: 4 - gradient_accumulation_steps: 8 - total_train_batch_size: 128 - total_eval_batch_size: 8 - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - 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 | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen | Nll Loss | Log Odds Ratio | Log Odds Chosen | |:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|:--------:|:--------------:|:---------------:| | 8.6911 | 0.4188 | 200 | 1.0935 | -0.0086 | -0.0106 | 0.6100 | 0.0020 | -1.0645 | -0.8642 | 2.0572 | 2.0427 | 1.1233 | -0.6611 | 0.3058 | | 8.6763 | 0.8377 | 400 | 1.0784 | -0.0085 | -0.0105 | 0.6060 | 0.0020 | -1.0496 | -0.8523 | 2.1915 | 2.1569 | 1.1100 | -0.6630 | 0.3031 | ### Framework versions - Transformers 4.51.0 - Pytorch 2.3.1+cu121 - Datasets 2.21.0 - Tokenizers 0.21.4