This model is a fine-tuned version of llava-hf/llava-v1.6-mistral-7b-hf on the AA_preference_cosi_0_50 dataset. It achieves the following results on the evaluation set:

Loss: 0.5580
Rewards/chosen: 1.1191
Rewards/rejected: -1.7161
Rewards/accuracies: 0.8125
Rewards/margins: 2.8352
Logps/rejected: -229.3270
Logps/chosen: -253.4991
Logits/rejected: -2.2872
Logits/chosen: -2.3146

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
0.5248	0.7463	50	0.5636	0.7981	-0.7376	0.7625	1.5357	-219.5417	-256.7093	-2.1893	-2.2123
0.2521	1.4925	100	0.5887	1.3477	-1.2511	0.8042	2.5988	-224.6767	-251.2128	-2.3607	-2.3766
0.1273	2.2388	150	0.5529	1.1944	-1.5829	0.8250	2.7773	-227.9948	-252.7459	-2.2852	-2.3106
0.1289	2.9851	200	0.5586	1.1189	-1.7195	0.8125	2.8384	-229.3605	-253.5011	-2.2866	-2.3140

Framework versions

Transformers 4.45.2
Pytorch 2.4.0+cu121
Datasets 2.21.0
Tokenizers 0.20.3

htlou/backup_0202_llamafactory_AA_preference_cosi_0_50-llava-mistral

AA_preference_cosi_0_50

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

htlou/
backup_0202_llamafactory_AA_preference_cosi_0_50-llava-mistral