library_name, base_model, tags, datasets, model-index

library_name	base_model	tags	datasets	model-index
transformers	qwen3-8b-base-sft-ultrachat-4xh200-batch-128-20260420-124036	alignment-handbook epsilon-dpo generated_from_trainer	HuggingFaceH4/ultrafeedback_binarized	name results qwen3-8b-base-epsilon-dpo-ultrafeedback-4xh200-batch-128-20260420-124036

qwen3-8b-base-epsilon-dpo-ultrafeedback-4xh200-batch-128-20260420-124036

This model is a fine-tuned version of qwen3-8b-base-sft-ultrachat-4xh200-batch-128-20260420-124036 on the HuggingFaceH4/ultrafeedback_binarized dataset. It achieves the following results on the evaluation set:

• Loss: 0.6403
• Epsilon Dpo/beta: 0.0021
• Epsilon Dpo/loss Margin Mean: 59.0314
• Epsilon Dpo/beta Margin Mean: 0.1219
• Epsilon Dpo/beta Margin Std: 0.2152
• Epsilon Dpo/beta Margin Grad Mean: -0.4699
• Epsilon Dpo/beta Margin Grad Std: 0.0531
• Rewards/chosen: -0.1383
• Rewards/rejected: -0.2601
• Rewards/accuracies: 0.7165
• Rewards/margins: 0.1219
• Logps/chosen: -346.2501
• Logps/rejected: -389.5577
• Logps/ref Chosen: -280.4283
• Logps/ref Rejected: -264.7045
• Logits/chosen: 1.5736
• Logits/rejected: 1.9569
• Kl/p Epsilon Steps: 0.7085
• Kl/n Epsilon Steps: 0.2855

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: 4
• eval_batch_size: 4
• seed: 42
• distributed_type: multi-GPU
• num_devices: 4
• gradient_accumulation_steps: 8
• total_train_batch_size: 128
• total_eval_batch_size: 16
• 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	Epsilon Dpo/beta	Epsilon Dpo/loss Margin Mean	Epsilon Dpo/beta Margin Mean	Epsilon Dpo/beta Margin Std	Epsilon Dpo/beta Margin Grad Mean	Epsilon Dpo/beta Margin Grad Std	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
5.0674	0.4188	200	0.6322	0.0051	28.6770	0.1452	0.2575	-0.4644	0.0631	-0.0590	-0.2042	0.7170	0.1452	-291.7776	-304.7309	-280.4283	-264.7045	1.8063	2.1551	0.6990	0.2930
5.1073	0.8377	400	0.6403	0.0021	59.0314	0.1219	0.2152	-0.4699	0.0531	-0.1383	-0.2601	0.7165	0.1219	-346.2501	-389.5577	-280.4283	-264.7045	1.5736	1.9569	0.7085	0.2855

Framework versions

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