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VK246/
IC_ver6J_coco_swin_gpt2_50B_1e

Name: IC_ver6J_coco_swin_gpt2_50B_1e
Availability: InStock

transformers

pytorch

vision-encoder-decoder

image-to-text

generated_from_trainer

coco

VK246/IC_ver6I_coco_swin_gpt2_50A_1e

finetune

endpoints_compatible

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IC_ver6J_coco_swin_gpt2_50B_1e

This model is a fine-tuned version of VK246/IC_ver6I_coco_swin_gpt2_50A_1e on the coco dataset. It achieves the following results on the evaluation set:

Loss: 0.8136
Cider: 72.7549
Rouge1: 41.4855
Rouge2: 16.0212
Rougel: 37.5584
Rougelsum: 37.557
Bleu-1: 42.5255
Bleu-2: 24.4018
Bleu-3: 15.3344
Bleu-4: 10.136
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
0.5339	0.34	1000	0.8717	70.3228	40.8259	15.4266	36.9266	36.9254	42.2006	23.9845	14.9776	9.8321	11.3063
0.6269	0.68	2000	0.8136	72.7549	41.4855	16.0212	37.5584	37.557	42.5255	24.4018	15.3344	10.136	11.3063

Framework versions

Transformers 4.32.0
Pytorch 2.0.1+cu118
Datasets 2.14.4
Tokenizers 0.13.3

VK246/IC_ver6J_coco_swin_gpt2_50B_1e

IC_ver6J_coco_swin_gpt2_50B_1e

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

VK246/
IC_ver6J_coco_swin_gpt2_50B_1e