blip-finetuned-gradcam-optimized

This model is a fine-tuned version of Salesforce/blip-image-captioning-large on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 6.6748

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: 2e-06
• train_batch_size: 2
• eval_batch_size: 2
• seed: 42
• gradient_accumulation_steps: 4
• total_train_batch_size: 8
• optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 50
• num_epochs: 15
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss
9.8985	0.4444	10	9.8608
9.7965	0.8889	20	9.7389
9.7009	1.3111	30	9.6374
9.539	1.7556	40	9.5101
8.2904	2.1778	50	9.1547
8.7882	2.6222	60	8.7516
7.6249	3.0444	70	8.4009
8.2185	3.4889	80	8.1483
8.0129	3.9333	90	7.9948
7.8556	4.3556	100	7.8385
7.7265	4.8	110	7.6990
7.6183	5.2222	120	7.5757
7.5	5.6667	130	7.4770
6.6711	6.0889	140	7.3812
7.3249	6.5333	150	7.3007
7.2369	6.9778	160	7.2224
7.1824	7.4	170	7.1548
7.1173	7.8444	180	7.0876
7.0568	8.2667	190	7.0291
7.0033	8.7111	200	6.9772
6.2525	9.1333	210	6.9274
6.9084	9.5778	220	6.8845
6.1803	10.0	230	6.8465
6.8372	10.4444	240	6.8137
6.807	10.8889	250	6.7842
6.7844	11.3111	260	6.7578
6.7499	11.7556	270	6.7369
6.0823	12.1778	280	6.7185
6.7188	12.6222	290	6.7038
6.036	13.0444	300	6.6918
6.7017	13.4889	310	6.6834
6.7003	13.9333	320	6.6776
6.6899	14.3556	330	6.6748

Framework versions

• Transformers 4.50.3
• Pytorch 2.6.0+cu124
• Datasets 3.5.0
• Tokenizers 0.21.1