This model is a fine-tuned version of llava-hf/llava-v1.6-mistral-7b-hf on the AA_preference_l0_new_step10_0_60 dataset. It achieves the following results on the evaluation set:

Loss: 0.5930
Rewards/chosen: 0.5295
Rewards/rejected: -1.8896
Rewards/accuracies: 0.7917
Rewards/margins: 2.4190
Logps/rejected: -242.2141
Logps/chosen: -237.5954
Logits/rejected: -2.0873
Logits/chosen: -2.1246

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: 1e-06
train_batch_size: 8
eval_batch_size: 8
seed: 42
distributed_type: multi-GPU
num_devices: 8
gradient_accumulation_steps: 4
total_train_batch_size: 256
total_eval_batch_size: 64
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: cosine
lr_scheduler_warmup_steps: 10
num_epochs: 3.0

Training results

Training Loss	Epoch	Step	Validation Loss	Rewards/chosen	Rewards/rejected	Rewards/accuracies	Rewards/margins	Logps/rejected	Logps/chosen	Logits/rejected	Logits/chosen
0.5728	0.6231	50	0.5968	0.7303	-0.4694	0.7257	1.1997	-228.0123	-235.5866	-2.3844	-2.3915
0.2338	1.2461	100	0.6138	0.8569	-1.0717	0.7708	1.9286	-234.0351	-234.3208	-2.3760	-2.3908
0.2653	1.8692	150	0.5830	0.4703	-1.7333	0.7847	2.2035	-240.6510	-238.1874	-2.0378	-2.0764
0.1596	2.4922	200	0.5909	0.5892	-1.8017	0.7951	2.3909	-241.3353	-236.9982	-2.0980	-2.1340

Framework versions

Transformers 4.45.2
Pytorch 2.4.0+cu121
Datasets 2.21.0
Tokenizers 0.20.3

htlou/mm-interp-AA_preference_l0_new_step10_0_60

AA_preference_l0_new_step10_0_60

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

htlou/
mm-interp-AA_preference_l0_new_step10_0_60