selfbiorag-7b-wo-kqa_golden-iter-dpo-step2

This model is a fine-tuned version of Minbyul/selfbiorag-7b-wo-kqa_golden-iter-sft-step1 on the HuggingFaceH4/ultrafeedback_binarized dataset. It achieves the following results on the evaluation set:

• Loss: 0.4028
• Rewards/chosen: -1.3389
• Rewards/rejected: -4.1640
• Rewards/accuracies: 0.7344
• Rewards/margins: 2.8251
• Logps/rejected: -858.1113
• Logps/chosen: -368.7221
• Logits/rejected: -0.8026
• Logits/chosen: -1.0600

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-06
• 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: 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
0.139	0.62	100	0.3923	-1.1034	-3.4359	0.7422	2.3325	-785.2989	-345.1770	-0.8936	-1.1380

Framework versions

• Transformers 4.39.0.dev0
• Pytorch 2.1.2
• Datasets 2.14.6
• Tokenizers 0.15.2