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-harmless-4xh200-batch-64-20260417-214452	alignment-handbook new-dpo generated_from_trainer	Anthropic/hh-rlhf	name results qwen3-8b-base-new-dpo-hh-harmless-4xh200-batch-64-q_t-0.45-s_star-0.4

qwen3-8b-base-new-dpo-hh-harmless-4xh200-batch-64-q_t-0.45-s_star-0.4

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

• Loss: 0.5698
• Fcm Dpo/beta: 0.0074
• Margin Dpo/margin Mean: 51.5411
• Margin Dpo/margin Std: 86.1362
• Logps/chosen: -172.7695
• Logps/rejected: -234.1051
• Logps/ref Chosen: -86.9018
• Logps/ref Rejected: -96.6964
• Logits/chosen: 1.3822
• Logits/rejected: 1.2498

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
1.3228	0.1512	100	0.6546	0.1000	0.8918	1.9761	-86.2353	-96.9216	-86.9018	-96.6964	1.6911	1.5774
1.1508	0.3023	200	0.5664	0.0827	5.5014	9.7680	-86.8311	-102.1271	-86.9018	-96.6964	1.6408	1.5124
1.1662	0.4535	300	0.5601	0.0232	19.9301	33.9240	-106.0360	-135.7607	-86.9018	-96.6964	1.3810	1.2532
1.2381	0.6047	400	0.5746	0.0092	39.8591	68.7826	-144.7731	-194.4268	-86.9018	-96.6964	1.7610	1.6208
1.1309	0.7559	500	0.5676	0.0079	51.0216	86.4987	-169.9242	-230.7403	-86.9018	-96.6964	1.5455	1.4084
1.183	0.9070	600	0.5698	0.0074	51.5411	86.1362	-172.7695	-234.1051	-86.9018	-96.6964	1.3822	1.2498

Framework versions

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