This model is a fine-tuned version of llava-hf/llava-v1.6-mistral-7b-hf on the RLAIF-V-Coccur-q0_25_preference dataset. It achieves the following results on the evaluation set:

Loss: 0.5440
Rewards/chosen: -2.3911
Rewards/rejected: -4.1460
Rewards/accuracies: 0.7188
Rewards/margins: 1.7550
Logps/rejected: -201.5194
Logps/chosen: -183.7933
Logits/rejected: -2.7049
Logits/chosen: -2.7311

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
0.5904	0.6944	50	0.5585	0.1767	-0.5308	0.6953	0.7075	-165.3675	-158.1156	-2.7400	-2.7505
0.2124	1.3889	100	0.5330	-0.9785	-2.2414	0.7344	1.2630	-182.4733	-169.6674	-2.6846	-2.7028
0.1027	2.0833	150	0.5209	-1.3289	-2.7382	0.7305	1.4093	-187.4415	-173.1719	-2.7648	-2.7841
0.0793	2.7778	200	0.5435	-2.3758	-4.1313	0.7227	1.7554	-201.3717	-183.6412	-2.7055	-2.7316

Framework versions

Transformers 4.45.2
Pytorch 2.4.0+cu121
Datasets 2.21.0
Tokenizers 0.20.3

htlou/mm-interp-RLAIF-V-Coccur-q0_25_preference

RLAIF-V-Coccur-q0_25_preference

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

htlou/
mm-interp-RLAIF-V-Coccur-q0_25_preference