seanyhan/qwen-3-8b-base-r-dpo-ultrafeedback-4xH200-batch-128-rerun-2-runpod

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qwen3-8b-base-r-dpo-ultrafeedback-4xh200-batch-128

This model is a fine-tuned version of 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: 0.5469
• —R Dpo/chosen Len: 294.4800
• —R Dpo/rejected Len: 249.8700
• —R Dpo/length Delta: 44.6100
• —R Dpo/regularization Term: 4.4610
• —Logps/chosen: -2936.7747
• —Logps/rejected: -2579.1685
• —Logps/ref Chosen: -281.4850
• —Logps/ref Rejected: -261.8005
• —Logits/chosen: 0.6320
• —Logits/rejected: 0.5334

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
• —trainbatchsize: 4
• —evalbatchsize: 4
• —seed: 42
• —distributed_type: multi-GPU
• —num_devices: 4
• —gradientaccumulationsteps: 8
• —totaltrainbatch_size: 128
• —totalevalbatch_size: 16
• —optimizer: Use OptimizerNames.ADAMWTORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizerargs=No additional optimizer arguments
• —lrschedulertype: cosine
• —lrschedulerwarmup_ratio: 0.1
• —num_epochs: 1

Training results

Framework versions

• —Transformers 4.51.0
• —Pytorch 2.3.1+cu121
• —Datasets 2.21.0
• —Tokenizers 0.21.4