This model is a fine-tuned version of dmis-lab/selfbiorag_7b on the HuggingFaceH4/ultrafeedback_binarized dataset. It achieves the following results on the evaluation set:

Loss: 0.6392
Rewards/chosen: 0.1232
Rewards/rejected: -0.0030
Rewards/accuracies: 0.7527
Rewards/margins: 0.1262
Logps/rejected: -171.6258
Logps/chosen: -150.9050
Logits/rejected: -1.5645
Logits/chosen: -1.7964

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: 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
0.6608	0.25	100	0.6631	0.1074	0.0395	0.7107	0.0680	-167.3843	-152.4830	-1.5362	-1.7612
0.6271	0.51	200	0.6474	0.1331	0.0272	0.7455	0.1060	-168.6118	-149.9109	-1.5243	-1.7495
0.61	0.76	300	0.6403	0.1251	0.0020	0.7554	0.1232	-171.1355	-150.7145	-1.5597	-1.7911

Framework versions

Transformers 4.39.0.dev0
Pytorch 2.1.2
Datasets 2.14.6
Tokenizers 0.15.2

Minbyul/selfbiorag-7b-dpo-full-wo-kqa_silver_wogold-ep3

selfbiorag-7b-dpo-full-wo-kqa_silver_wogold-ep3

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

Minbyul/
selfbiorag-7b-dpo-full-wo-kqa_silver_wogold-ep3