library_name, base_model, tags, datasets, model-index

library_name	base_model	tags	datasets	model-index
transformers	jackf857/qwen3-8b-base-sft-hh-helpful-4xh200-batch-64-20260417-214452	alignment-handbook epsilon-dpo generated_from_trainer	Anthropic/hh-rlhf	name results qwen3-8b-base-epsilon-dpo-hh-helpful-4xh200-batch-64-20260424-040306

qwen3-8b-base-epsilon-dpo-hh-helpful-4xh200-batch-64-20260424-040306

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: 0.5845
• Rewards/chosen: -0.6029
• Rewards/rejected: -0.8720
• Rewards/accuracies: 0.7568
• Rewards/margins: 0.2691
• Logps/chosen: -250.9089
• Logps/rejected: -312.3157
• Logps/ref Chosen: -100.4936
• Logps/ref Rejected: -94.0678
• Logits/chosen: -7.6179
• Logits/rejected: -7.2013
• Kl/p Epsilon Steps: 0.7466
• Kl/n Epsilon Steps: 0.2530

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	Rewards/chosen	Rewards/rejected	Rewards/accuracies	Rewards/margins	Logps/chosen	Logps/rejected	Logps/ref Chosen	Logps/ref Rejected	Logits/chosen	Logits/rejected	Kl/p Epsilon Steps	Kl/n Epsilon Steps
1.1171	0.1468	100	0.6201	-0.3131	-0.5532	0.6841	0.2401	-104.8254	-101.7906	-100.4936	-94.0678	-3.1086	-2.4245	0.6134	0.3857
0.9014	0.2937	200	0.5126	-0.9392	-1.5651	0.7620	0.6259	-122.0199	-130.1003	-100.4936	-94.0678	-5.9108	-5.5656	0.6905	0.3069
0.912	0.4405	300	0.4875	-1.6289	-2.3480	0.7787	0.7190	-167.7714	-191.3218	-100.4936	-94.0678	-7.0070	-6.7219	0.7509	0.2470
0.7868	0.5874	400	0.4938	-1.5799	-2.2534	0.7791	0.6735	-222.8989	-269.1398	-100.4936	-94.0678	-7.4780	-7.1188	0.7646	0.2342
1.0563	0.7342	500	0.5370	-1.0135	-1.4612	0.7667	0.4477	-242.7305	-299.7766	-100.4936	-94.0678	-7.5872	-7.1850	0.7491	0.2504
1.1296	0.8811	600	0.5845	-0.6029	-0.8720	0.7568	0.2691	-250.9089	-312.3157	-100.4936	-94.0678	-7.6179	-7.2013	0.7466	0.2530

Framework versions

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