This model is a fine-tuned version of jackf857/qwen3-8b-base-sft-hh-helpful-4xh200-batch-64-20260417-214452 on the Anthropic/hh-rlhf dataset. It achieves the following results on the evaluation set:

Model description

More information needed

Intended uses & limitations

More information needed

More information needed

The following hyperparameters were used during training:

learning_rate: 5e-07
train_batch_size: 8
eval_batch_size: 8
seed: 42
distributed_type: multi-GPU
num_devices: 4
gradient_accumulation_steps: 2
total_train_batch_size: 64
total_eval_batch_size: 32
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 Loss	Epoch	Step	Validation Loss	Fcm Dpo/beta	Margin Dpo/margin Mean	Margin Dpo/margin Std	Logps/chosen	Logps/rejected	Logps/ref Chosen	Logps/ref Rejected	Logits/chosen	Logits/rejected
0.8851	0.1468	100	0.5619	0.1911	2.7888	5.1863	-102.8106	-99.1735	-100.4936	-94.0678	-0.0489	0.1697
0.8588	0.2937	200	0.5018	0.0551	12.3878	17.0440	-115.7780	-121.7400	-100.4936	-94.0678	-1.1454	-0.8443
0.9115	0.4405	300	0.4888	0.0264	26.5166	33.8690	-155.7471	-175.8378	-100.4936	-94.0678	-1.7435	-1.4186
0.8025	0.5874	400	0.4957	0.0127	51.4539	65.7573	-216.1685	-261.1965	-100.4936	-94.0678	-1.7851	-1.4226
0.9588	0.7342	500	0.4848	0.0130	58.4689	75.4513	-233.7258	-285.7689	-100.4936	-94.0678	-1.8270	-1.4568
0.8671	0.8811	600	0.4843	0.0126	59.3348	75.8064	-239.6379	-292.5469	-100.4936	-94.0678	-1.6991	-1.3195