IC_ver1_coco_swin_gpt2_5pc_2e

VK246/IC_ver1_coco_swin_gpt2_5pc_2e

IC_ver1_coco_swin_gpt2_5pc_2e is a image-text-to-text model from VK246. 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 7, 2023
Updated: Jul 7, 2023
SHA: 3f23d01a

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Datasets

coco

Model card

From the Hugging Face model README

IC_ver1_coco_swin_gpt2_5pc_2e

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

Loss: 0.9700
Rouge1: 36.317
Rouge2: 12.0175
Rougel: 33.7883
Rougelsum: 33.7342
Bleu: 6.5392
Gen Len: 11.2887

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: 100
eval_batch_size: 100
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 2

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum	Bleu	Gen Len
1.29	0.71	200	1.0273	33.6256	10.3076	31.0868	31.0562	5.5088	11.2887
1.0193	1.41	400	0.9700	36.317	12.0175	33.7883	33.7342	6.5392	11.2887

Framework versions

Transformers 4.30.2
Pytorch 2.0.1+cu118
Datasets 2.13.1
Tokenizers 0.13.3

Task: Image-Text-to-Text
Library: transformers
Type: vision-encoder-decoder
Created: Jul 7, 2023
Updated: Jul 7, 2023