Downloads · 30 days
9
4% of all-time downloads
IC_ver6b_coco_swin_gpt2_50Bpc_1e
VK246/IC_ver6b_coco_swin_gpt2_50Bpc_1e
IC_ver6b_coco_swin_gpt2_50Bpc_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. --
All-time downloads
214
Public
Repo size
6.7 GB
Likes
0
Public
Repo makeup
Click a slice to open those files.
.bin962 MB · 99%
At a glance
- Task
- Image-Text-to-Text
- Library
- transformers
- Model type
- vision-encoder-decoder
- Access
- Public
- Created
- Jul 13, 2023
- Updated
- Jul 13, 2023
- SHA
- f758c30f
Try a prompt
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_ver6b_coco_swin_gpt2_50Bpc_1e
This model is a fine-tuned version of VK246/IC_ver6a_coco_swin_gpt2_50Apc_1e on the coco dataset. It achieves the following results on the evaluation set:
- Loss: 0.8180
- Rouge1: 41.462
- Rouge2: 16.1291
- Rougel: 37.6518
- Rougelsum: 37.6471
- Bleu: 9.9643
- 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 | Rouge1 | Rouge2 | Rougel | Rougelsum | Bleu | Gen Len |
|---|---|---|---|---|---|---|---|---|---|
| 0.8889 | 0.17 | 500 | 0.8659 | 39.7654 | 14.603 | 36.1709 | 36.1638 | 8.8491 | 11.3063 |
| 0.8756 | 0.34 | 1000 | 0.8515 | 40.3678 | 15.2852 | 36.7303 | 36.7188 | 9.3029 | 11.3063 |
| 0.862 | 0.51 | 1500 | 0.8388 | 40.7537 | 15.2635 | 37.0523 | 37.0379 | 9.3057 | 11.3063 |
| 0.8546 | 0.68 | 2000 | 0.8281 | 40.961 | 15.6192 | 37.1627 | 37.1546 | 9.7453 | 11.3063 |
| 0.837 | 0.85 | 2500 | 0.8214 | 41.5703 | 16.1006 | 37.7767 | 37.7654 | 9.9062 | 11.3063 |
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 13, 2023
- Updated
- Jul 13, 2023