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VK246/
IC_ver6P_coco_swin_gpt2_50B_1e

Name: IC_ver6P_coco_swin_gpt2_50B_1e
Availability: InStock

transformers

pytorch

vision-encoder-decoder

image-to-text

generated_from_trainer

coco

VK246/IC_ver6O_coco_swin_gpt2_50A_1e

finetune

endpoints_compatible

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IC_ver6P_coco_swin_gpt2_50B_1e

This model is a fine-tuned version of VK246/IC_ver6O_coco_swin_gpt2_50A_1e on the coco dataset. It achieves the following results on the evaluation set:

Loss: 0.9083
Cider: 71.9821
Rouge1: 40.8231
Rouge2: 15.3858
Rougel: 36.9192
Rougelsum: 36.9129
Bleu-1: 42.0506
Bleu-2: 23.8307
Bleu-3: 14.8432
Bleu-4: 9.7337
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
0.3172	0.34	1000	1.0778	66.318	39.4397	14.0713	35.6057	35.6047	40.7003	22.4525	13.6705	8.7851	11.3063
0.4589	0.68	2000	0.9083	71.9821	40.8231	15.3858	36.9192	36.9129	42.0506	23.8307	14.8432	9.7337	11.3063

Framework versions

Transformers 4.32.0
Pytorch 2.0.1+cu118
Datasets 2.14.4
Tokenizers 0.13.3

VK246/IC_ver6P_coco_swin_gpt2_50B_1e

IC_ver6P_coco_swin_gpt2_50B_1e

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

VK246/
IC_ver6P_coco_swin_gpt2_50B_1e