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-0.6

qwen3-8b-base-new-dpo-hh-helpful-4xh200-batch-64-q_t-0.45-s_star-0.6

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: 0.5224
• Fcm Dpo/beta: 0.0073
• Margin Dpo/margin Mean: 73.6023
• Margin Dpo/margin Std: 100.2118
• Logps/chosen: -265.1147
• Logps/rejected: -332.2911
• Logps/ref Chosen: -100.4936
• Logps/ref Rejected: -94.0678
• Logits/chosen: -1.8407
• Logits/rejected: -1.4555

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
0.9831	0.1468	100	0.5851	0.1290	3.0273	6.0741	-103.4172	-100.0187	-100.4936	-94.0678	0.0310	0.2743
0.9603	0.2937	200	0.5345	0.0330	15.0670	21.7615	-123.5883	-132.2295	-100.4936	-94.0678	-1.4398	-1.1262
1.0079	0.4405	300	0.5175	0.0128	42.6819	56.6599	-199.0951	-235.3512	-100.4936	-94.0678	-1.7159	-1.3591
0.9031	0.5874	400	0.5321	0.0072	66.1747	89.8270	-255.0186	-314.7675	-100.4936	-94.0678	-1.9564	-1.5863
1.0372	0.7342	500	0.5229	0.0074	72.2195	99.1610	-264.5698	-330.3635	-100.4936	-94.0678	-1.9734	-1.5979
0.9868	0.8811	600	0.5224	0.0073	73.6023	100.2118	-265.1147	-332.2911	-100.4936	-94.0678	-1.8407	-1.4555

Framework versions

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