zephyr-7b-dpo-full

This model is a fine-tuned version of alignment-handbook/zephyr-7b-sft-full on the HuggingFaceH4/ultrafeedback_binarized dataset. It achieves the following results on the evaluation set:

• Loss: 0.5042
• Rewards/chosen: -1.0500
• Rewards/rejected: -2.0480
• Rewards/accuracies: 0.7539
• Rewards/margins: 0.9980
• Logps/rejected: -468.1450
• Logps/chosen: -368.4135
• Logits/rejected: 2.3821
• Logits/chosen: 1.6141

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: 8
• gradient_accumulation_steps: 2
• total_train_batch_size: 128
• total_eval_batch_size: 64
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• 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/rejected	Logps/chosen	Logits/rejected	Logits/chosen
0.5723	0.21	100	0.5851	-0.4097	-0.8752	0.7031	0.4655	-350.8695	-304.3812	-2.3494	-2.4070
0.5084	0.42	200	0.5251	-0.9116	-1.7472	0.7422	0.8355	-438.0663	-354.5790	1.3918	0.9248
0.5059	0.63	300	0.5130	-0.8646	-1.7542	0.75	0.8896	-438.7735	-349.8758	2.0331	1.2558
0.4853	0.84	400	0.5050	-1.0929	-2.1085	0.7539	1.0156	-474.1963	-372.7067	2.5922	1.8194

Framework versions

• Transformers 4.36.2
• Pytorch 2.1.2+cu121
• Datasets 2.14.6
• Tokenizers 0.15.0