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VK246/
IC_ver6G_coco_swin_gpt2_50A_1e

Name: IC_ver6G_coco_swin_gpt2_50A_1e
Availability: InStock

transformers

pytorch

tensorboard

vision-encoder-decoder

image-to-text

generated_from_trainer

coco

VK246/IC_ver6F_coco_swin_gpt2_50B_1e

finetune

endpoints_compatible

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IC_ver6G_coco_swin_gpt2_50A_1e

This model is a fine-tuned version of VK246/IC_ver6F_coco_swin_gpt2_50B_1e on the coco dataset. It achieves the following results on the evaluation set:

Loss: 0.7892
Cider: 15.3553
Rouge1: 41.9548
Rouge2: 16.3636
Rougel: 38.1268
Rougelsum: 38.1269
Bleu-1: 42.7082
Bleu-2: 24.7427
Bleu-3: 15.632
Bleu-4: 10.351
Gen Len: 11.2806

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
0.6462	0.34	1000	0.8195	16.4275	41.2411	15.6826	37.4271	37.4332	42.1612	24.0307	15.0144	9.8204	11.2806
0.6923	0.68	2000	0.7892	15.3553	41.9548	16.3636	38.1268	38.1269	42.7082	24.7427	15.632	10.351	11.2806

Framework versions

Transformers 4.31.0
Pytorch 2.0.1+cu118
Datasets 2.14.4
Tokenizers 0.13.3

VK246/IC_ver6G_coco_swin_gpt2_50A_1e

IC_ver6G_coco_swin_gpt2_50A_1e

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

VK246/
IC_ver6G_coco_swin_gpt2_50A_1e