swin-gpt-NWPU-captioning

swadhindas324/swin-gpt-NWPU-captioning

swin-gpt-NWPU-captioning is a image-text-to-text model from swadhindas324. Use it for the image-text-to-text task on the model card, and read the license before you ship it in a product. It is set up for transformers.

should probably proofread and complete it, then remove this comment. --

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At a glance

Task: Image-Text-to-Text
Library: transformers
Model type: vision-encoder-decoder
Access: Public
Created: Jul 1, 2026
Updated: Jul 1, 2026
SHA: 8c6dc4ac

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Model card

From the Hugging Face model README

swin-gpt-NWPU-captioning

This model is a fine-tuned version of on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.5339
Accuracy: 85.19
Bleu-1: 0.8630
Bleu-2: 0.7745
Bleu-3: 0.7039
Bleu-4: 0.6472
Meteor: 0.7734
Rouge-l: 0.7624
Cider: 1.8392

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: 0.0001
train_batch_size: 64
eval_batch_size: 64
seed: 50
optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED 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: 1024
num_epochs: 128
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Bleu-1	Bleu-2	Bleu-3	Bleu-4	Meteor	Rouge-l	Cider
0.7902	1.0	1969	0.4962	85.07	0.8231	0.7203	0.6407	0.5778	0.7196	0.7062	1.6480
0.4833	2.0	3938	0.4726	84.85	0.8344	0.7345	0.6529	0.5878	0.7337	0.7202	1.6506
0.4490	3.0	5907	0.4691	85.1	0.8574	0.7657	0.6910	0.6307	0.7639	0.7486	1.7462
0.4245	4.0	7876	0.4678	84.65	0.8572	0.7685	0.6960	0.6376	0.7748	0.7565	1.7604
0.4068	5.0	9845	0.4723	85.14	0.8616	0.7719	0.6995	0.6414	0.7781	0.7632	1.8423
0.3889	6.0	11814	0.4778	85.36	0.8691	0.7861	0.7186	0.6639	0.7755	0.7698	1.8639
0.3711	7.0	13783	0.4849	85.0	0.8599	0.7701	0.6981	0.6398	0.7815	0.7663	1.8020
0.3553	8.0	15752	0.4919	85.26	0.8672	0.7788	0.7071	0.6489	0.7775	0.7667	1.8345
0.3396	9.0	17721	0.5033	85.1	0.8621	0.7749	0.7052	0.6490	0.7690	0.7617	1.8219
0.3230	10.0	19690	0.5192	85.21	0.8592	0.7720	0.7017	0.6441	0.7736	0.7631	1.8233
0.3088	11.0	21659	0.5339	85.19	0.8630	0.7745	0.7039	0.6472	0.7734	0.7624	1.8392

Framework versions

Transformers 5.12.1
Pytorch 2.12.1+cu130
Datasets 5.0.0
Tokenizers 0.22.2

Task: Image-Text-to-Text
Library: transformers
Type: vision-encoder-decoder
Created: Jul 1, 2026
Updated: Jul 1, 2026