Bitamin_mutimodal

This model is a fine-tuned version of ddobokki/vision-encoder-decoder-vit-gpt2-coco-ko on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 0.0644
• Rouge1: 6.6906
• Rouge2: 3.2986
• Rougel: 6.6499
• Rougelsum: 6.6803
• Gen Len: 100.0

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: 5e-05
• train_batch_size: 4
• eval_batch_size: 4
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 5

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum	Gen Len
0.2001	1.0	2982	0.1589	0.0	0.0	0.0	0.0	100.0
0.1178	2.0	5964	0.1095	0.8554	0.7275	0.8315	0.8554	100.0
0.0778	3.0	8946	0.0829	2.7168	1.6458	2.7157	2.6864	100.0
0.0552	4.0	11928	0.0691	5.454	2.6068	5.4184	5.4101	100.0
0.0396	5.0	14910	0.0644	6.6906	3.2986	6.6499	6.6803	100.0

Framework versions

• Transformers 4.42.3
• Pytorch 2.1.2
• Datasets 2.20.0
• Tokenizers 0.19.1