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IC_ver6trial_coco_swin_gpt2_50Apc_1e
VK246/IC_ver6trial_coco_swin_gpt2_50Apc_1e
IC_ver6trial_coco_swin_gpt2_50Apc_1e 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
- Aug 17, 2023
- Updated
- Aug 17, 2023
- SHA
- 3ad0159a
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Base models
Datasets
Model card
From the Hugging Face model README
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
IC_ver6trial_coco_swin_gpt2_50Apc_1e
This model is a fine-tuned version of VK246/IC_ver6d_coco_swin_gpt2_50Bpc_1e on the coco dataset. It achieves the following results on the evaluation set:
- Loss: 0.8113
- Cider: 43.6787
- Rouge1: 41.4057
- Rouge2: 16.177
- Rougel: 38.9636
- Rougelsum: 38.8335
- Bleu-1: 43.1153
- Bleu-2: 24.9997
- Bleu-3: 15.7558
- Bleu-4: 10.4674
- Gen Len: 11.1124
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
Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3
- Task
- Image-Text-to-Text
- Library
- transformers
- Type
- vision-encoder-decoder
- Created
- Aug 17, 2023
- Updated
- Aug 17, 2023