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IC_ver3a_coco_swin_gpt2_
VK246/IC_ver3a_coco_swin_gpt2_
IC_ver3a_coco_swin_gpt2_ 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
- Jul 9, 2023
- Updated
- Jul 9, 2023
- SHA
- 136bd0fc
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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_ver3a_coco_swin_gpt2_
This model is a fine-tuned version of on the coco dataset. It achieves the following results on the evaluation set:
- Loss: 1.0156
- Rouge1: 33.8659
- Rouge2: 10.1039
- Rougel: 31.4861
- Rougelsum: 31.4905
- Bleu: 5.7396
- Gen Len: 11.2887
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 | Rouge1 | Rouge2 | Rougel | Rougelsum | Bleu | Gen Len |
|---|---|---|---|---|---|---|---|---|---|
| 1.4761 | 0.34 | 100 | 1.1047 | 28.2757 | 6.0267 | 26.4732 | 26.5071 | 2.7859 | 11.2887 |
| 1.1238 | 0.68 | 200 | 1.0406 | 32.0448 | 8.6347 | 29.6117 | 29.6193 | 4.4174 | 11.2887 |
Framework versions
- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3
- Task
- Image-Text-to-Text
- Library
- transformers
- Type
- vision-encoder-decoder
- Created
- Jul 9, 2023
- Updated
- Jul 9, 2023