This model is a fine-tuned version of 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: 0.5897
Beta Dpo/gap Mean: 23.0136
Beta Dpo/gap Std: 39.9127
Beta Dpo/beta Used Raw: 0.0146
Beta Dpo/beta Used: 0.0335
Beta Dpo/mask Keep Frac: 1.0
Logits/chosen: 1.5098
Logits/rejected: 1.5463

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	Beta Dpo/gap Mean	Beta Dpo/gap Std	Beta Dpo/beta Used Raw	Beta Dpo/beta Used	Beta Dpo/mask Keep Frac	Logits/chosen	Logits/rejected
4.6811	0.4188	200	0.5822	17.3495	36.2958	0.0115	0.0273	1.0	1.4601	1.4735
4.2926	0.8377	400	0.5897	23.0136	39.9127	0.0146	0.0335	1.0	1.5098	1.5463

Framework versions

Transformers 4.51.0
Pytorch 2.3.1+cu121
Datasets 2.21.0
Tokenizers 0.21.4

W-61/qwen3-8b-base-beta-dpo-ultrafeedback-4xh200-batch-128-20260423-040315

qwen3-8b-base-beta-dpo-ultrafeedback-4xh200-batch-128-20260423-040315

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

W-61/
qwen3-8b-base-beta-dpo-ultrafeedback-4xh200-batch-128-20260423-040315