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: 0.6355
Rewards/chosen: 0.1376
Rewards/rejected: -0.0007
Rewards/accuracies: 0.7326
Rewards/margins: 0.1383
Logps/rejected: -144.1728
Logps/chosen: -121.3669
Logits/rejected: -1.5473
Logits/chosen: -1.8108

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	Logits/chosen	Logits/rejected	Logps/chosen	Logps/rejected	Validation Loss	Rewards/accuracies	Rewards/chosen	Rewards/margins	Rewards/rejected
0.6595	0.22	100	-1.7720	-1.4957	-124.0620	-139.3042	0.6647	0.6875	0.1107	0.0627	0.0480
0.6273	0.45	200	-1.7316	-1.4653	-119.3853	-138.4957	0.6494	0.6979	0.1574	0.1013	0.0561
0.6009	0.67	300	-1.7770	-1.5098	-120.2743	-141.8649	0.6398	0.7188	0.1485	0.1262	0.0224
0.6003	0.9	400	-1.8108	-1.5449	-121.3720	-144.0564	0.6355	0.7326	0.1376	0.1371	0.0005

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_golden-ep3

selfbiorag-7b-dpo-full-wo-kqa_golden-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_golden-ep3