zephyr-7b-dpo-full

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

• Loss: 0.5148
• Rewards/chosen: -0.9764
• Rewards/rejected: -1.9505
• Rewards/accuracies: 0.7656
• Rewards/margins: 0.9741
• Logps/rejected: -460.4252
• Logps/chosen: -362.5974
• Logits/rejected: 3.5330
• Logits/chosen: 3.0354

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
0.5965	0.21	100	0.6008	-0.4349	-0.7957	0.7148	0.3608	-344.9378	-308.4434	-2.0640	-2.1194
0.5688	0.42	200	0.5589	-0.6365	-1.1670	0.7383	0.5305	-382.0739	-328.6037	-1.1455	-1.2654
0.5121	0.63	300	0.5288	-0.6931	-1.5300	0.7617	0.8370	-418.3772	-334.2621	2.1389	1.7225
0.5208	0.84	400	0.5153	-0.8705	-1.8050	0.7578	0.9345	-445.8741	-352.0043	3.4324	2.9372

Framework versions

• Transformers 4.39.3
• Pytorch 2.3.0+cu121
• Datasets 2.19.1
• Tokenizers 0.15.2