This model is a fine-tuned version of princeton-nlp/Llama-3-Base-8B-SFT on the HuggingFaceH4/ultrafeedback_binarized dataset. It achieves the following results on the evaluation set:

Loss: 0.5487
Rewards/chosen: -1.1436
Rewards/rejected: -1.6789
Rewards/accuracies: 0.7380
Rewards/margins: 0.5353
Logps/rejected: -435.4569
Logps/chosen: -405.1720
Logits/rejected: -0.7446
Logits/chosen: -0.7091

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: 1
eval_batch_size: 1
seed: 42
distributed_type: multi-GPU
num_devices: 4
gradient_accumulation_steps: 32
total_train_batch_size: 128
total_eval_batch_size: 4
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
0.6829	0.1047	50	0.6802	0.0612	0.0336	0.6580	0.0276	-264.2072	-284.6938	-0.7278	-0.6508
0.6237	0.2094	100	0.6211	-0.1187	-0.3023	0.7080	0.1836	-297.7958	-302.6812	-0.7410	-0.6815
0.5943	0.3141	150	0.5984	-0.2406	-0.5058	0.6980	0.2653	-318.1529	-314.8689	-0.7015	-0.6515
0.5788	0.4187	200	0.5731	-0.6524	-1.0298	0.7100	0.3774	-370.5502	-356.0472	-0.7012	-0.6568
0.5518	0.5234	250	0.5652	-1.0017	-1.4643	0.7260	0.4627	-414.0016	-390.9777	-0.7286	-0.6885
0.5472	0.6281	300	0.5599	-1.0502	-1.5173	0.7220	0.4671	-419.2986	-395.8287	-0.7269	-0.6862
0.5215	0.7328	350	0.5506	-1.0201	-1.5402	0.7380	0.5201	-421.5936	-392.8219	-0.7402	-0.7031
0.5415	0.8375	400	0.5494	-1.1153	-1.6479	0.7460	0.5326	-432.3640	-402.3448	-0.7419	-0.7055
0.5368	0.9422	450	0.5487	-1.1436	-1.6789	0.7380	0.5353	-435.4569	-405.1720	-0.7446	-0.7091

Framework versions

Transformers 4.44.2
Pytorch 2.4.0+cu121
Datasets 2.21.0
Tokenizers 0.19.1

NoManDeRY/DPO-Shift-Llama-3-8B-Ultrafeedback-fixed-1.0

Llama-3-dpo-5e-7-SFTed-paged_adamw_32bit-1.0

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

NoManDeRY/
DPO-Shift-Llama-3-8B-Ultrafeedback-fixed-1.0