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VK246/
IC_ver6L_coco_swin_gpt2_50B_1e

Name: IC_ver6L_coco_swin_gpt2_50B_1e
Availability: InStock

transformers

pytorch

vision-encoder-decoder

image-to-text

generated_from_trainer

coco

VK246/IC_ver6K_coco_swin_gpt2_50A_1e

finetune

endpoints_compatible

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IC_ver6L_coco_swin_gpt2_50B_1e

This model is a fine-tuned version of VK246/IC_ver6K_coco_swin_gpt2_50A_1e on the coco dataset. It achieves the following results on the evaluation set:

Loss: 0.8371
Cider: 72.6054
Rouge1: 41.2906
Rouge2: 15.8851
Rougel: 37.3963
Rougelsum: 37.4014
Bleu-1: 42.3937
Bleu-2: 24.3104
Bleu-3: 15.291
Bleu-4: 10.0894
Gen Len: 11.3063

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: 96
eval_batch_size: 96
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 1

Training results

Training Loss	Epoch	Step	Validation Loss	Cider	Rouge1	Rouge2	Rougel	Rougelsum	Bleu-1	Bleu-2	Bleu-3	Bleu-4	Gen Len
0.4535	0.34	1000	0.9282	70.2558	40.6455	15.1383	36.6998	36.6999	41.838	23.6151	14.6823	9.6083	11.3063
0.5716	0.68	2000	0.8371	72.6054	41.2906	15.8851	37.3963	37.4014	42.3937	24.3104	15.291	10.0894	11.3063

Framework versions

Transformers 4.32.0
Pytorch 2.0.1+cu118
Datasets 2.14.4
Tokenizers 0.13.3

VK246/IC_ver6L_coco_swin_gpt2_50B_1e

IC_ver6L_coco_swin_gpt2_50B_1e

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

VK246/
IC_ver6L_coco_swin_gpt2_50B_1e