library_name, license, base_model, tags, datasets, model-index

library_name	license	base_model	tags	datasets	model-index
transformers	apache-2.0	jackf857/qwen3-8b-base-sft-hh-helpful-4xh200-batch-64-20260417-214452	alignment-handbook new-dpo generated_from_trainer	Anthropic/hh-rlhf	name results qwen3-8b-base-new-dpo-hh-helpful-4xh200-batch-64-q_t-0.45-s_star-0.85

qwen3-8b-base-new-dpo-hh-helpful-4xh200-batch-64-q_t-0.45-s_star-0.85

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:

• Loss: 0.4843
• Fcm Dpo/beta: 0.0126
• Margin Dpo/margin Mean: 59.3348
• Margin Dpo/margin Std: 75.8064
• Logps/chosen: -239.6379
• Logps/rejected: -292.5469
• Logps/ref Chosen: -100.4936
• Logps/ref Rejected: -94.0678
• Logits/chosen: -1.6991
• Logits/rejected: -1.3195

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: 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 results

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

Framework versions

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