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IC_ver6M_coco_swin_gpt2_50A_1e
VK246/IC_ver6M_coco_swin_gpt2_50A_1e
IC_ver6M_coco_swin_gpt2_50A_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 23, 2023
- Updated
- Aug 23, 2023
- SHA
- b3c92e6c
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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_ver6M_coco_swin_gpt2_50A_1e
This model is a fine-tuned version of VK246/IC_ver6L_coco_swin_gpt2_50B_1e on the coco dataset. It achieves the following results on the evaluation set:
- Loss: 0.8502
- Cider: 74.2614
- Rouge1: 41.2346
- Rouge2: 15.6726
- Rougel: 37.3373
- Rougelsum: 37.3448
- Bleu-1: 42.1725
- Bleu-2: 24.0988
- Bleu-3: 15.0597
- Bleu-4: 9.8745
- 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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.4052 | 0.34 | 1000 | 0.9934 | 68.6639 | 39.9165 | 14.5681 | 36.2437 | 36.2466 | 41.4603 | 23.2118 | 14.2892 | 9.3187 | 11.2806 |
| 0.5281 | 0.68 | 2000 | 0.8502 | 74.2614 | 41.2346 | 15.6726 | 37.3373 | 37.3448 | 42.1725 | 24.0988 | 15.0597 | 9.8745 | 11.2806 |
Framework versions
- Transformers 4.32.0
- 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 23, 2023
- Updated
- Aug 23, 2023