--- library_name: transformers base_model: W-61/qwen3-8b-base-sft-ultrachat-4xh200-batch-128 tags: - alignment-handbook - margin-dpo - generated_from_trainer datasets: - HuggingFaceH4/ultrafeedback_binarized model-index: - name: qwen3-8b-base-margin-dpo-ultrafeedback-4xh200-batch-128-20260423-040315 results: [] --- # qwen3-8b-base-margin-dpo-ultrafeedback-4xh200-batch-128-20260423-040315 This model is a fine-tuned version of [W-61/qwen3-8b-base-sft-ultrachat-4xh200-batch-128](https://huggingface.co/W-61/qwen3-8b-base-sft-ultrachat-4xh200-batch-128) on the HuggingFaceH4/ultrafeedback_binarized dataset. It achieves the following results on the evaluation set: - Loss: 0.5602 - Margin Dpo/margin Mean: 48.7131 - Margin Dpo/margin Std: 68.1546 - Logps/chosen: -316.0414 - Logps/rejected: -345.1451 - Logps/ref Chosen: -281.4589 - Logps/ref Rejected: -261.8495 - Logits/chosen: 1.1933 - Logits/rejected: 1.2367 ## 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: 4 - seed: 42 - distributed_type: multi-GPU - num_devices: 4 - gradient_accumulation_steps: 8 - total_train_batch_size: 128 - total_eval_batch_size: 16 - 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 | Margin Dpo/margin Mean | Margin Dpo/margin Std | Logps/chosen | Logps/rejected | Logps/ref Chosen | Logps/ref Rejected | Logits/chosen | Logits/rejected | |:-------------:|:------:|:----:|:---------------:|:----------------------:|:---------------------:|:------------:|:--------------:|:----------------:|:------------------:|:-------------:|:---------------:| | 4.9383 | 0.4188 | 200 | 0.5970 | 28.2584 | 39.0244 | -287.0227 | -295.6718 | -281.4589 | -261.8495 | 1.4300 | 1.4697 | | 4.2739 | 0.8377 | 400 | 0.5602 | 48.7131 | 68.1546 | -316.0414 | -345.1451 | -281.4589 | -261.8495 | 1.1933 | 1.2367 | ### Framework versions - Transformers 4.51.0 - Pytorch 2.3.1+cu121 - Datasets 2.21.0 - Tokenizers 0.21.4