htlou/mm-interp-AA_preference_l0_0_75

AA_preference_l0_0_75

This model is a fine-tuned version of llava-hf/llava-v1.6-mistral-7b-hf on the AA_preference_l0_0_75 dataset. It achieves the following results on the evaluation set:

• Loss: 0.5643
• Rewards/chosen: 1.3942
• Rewards/rejected: -0.7947
• Rewards/accuracies: 0.8000
• Rewards/margins: 2.1889
• Logps/rejected: -224.1609
• Logps/chosen: -246.0838
• Logits/rejected: -2.3264
• Logits/chosen: -2.3596

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
0.5946	0.7463	50	0.5850	1.2899	-0.0802	0.7333	1.3701	-217.0163	-247.1266	-2.3881	-2.4191
0.255	1.4925	100	0.5857	1.4526	-0.5760	0.7958	2.0286	-221.9741	-245.4996	-2.4099	-2.4342
0.1492	2.2388	150	0.5706	1.4938	-0.5466	0.7917	2.0403	-221.6795	-245.0877	-2.3284	-2.3634
0.1536	2.9851	200	0.5642	1.3949	-0.7954	0.7917	2.1903	-224.1678	-246.0766	-2.3262	-2.3595

Framework versions

• Transformers 4.45.2
• Pytorch 2.4.0+cu121
• Datasets 2.21.0
• Tokenizers 0.20.3