Downloads · 30 days
13
6% of all-time downloads
IC_ver6G_coco_swin_gpt2_50A_1e
VK246/IC_ver6G_coco_swin_gpt2_50A_1e
IC_ver6G_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. --
All-time downloads
218
Public
Repo size
3.9 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
- Aug 21, 2023
- Updated
- Aug 21, 2023
- SHA
- d6fe3f39
Try a prompt
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_ver6G_coco_swin_gpt2_50A_1e
This model is a fine-tuned version of VK246/IC_ver6F_coco_swin_gpt2_50B_1e on the coco dataset. It achieves the following results on the evaluation set:
- Loss: 0.7892
- Cider: 15.3553
- Rouge1: 41.9548
- Rouge2: 16.3636
- Rougel: 38.1268
- Rougelsum: 38.1269
- Bleu-1: 42.7082
- Bleu-2: 24.7427
- Bleu-3: 15.632
- Bleu-4: 10.351
- 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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.6462 | 0.34 | 1000 | 0.8195 | 16.4275 | 41.2411 | 15.6826 | 37.4271 | 37.4332 | 42.1612 | 24.0307 | 15.0144 | 9.8204 | 11.2806 |
| 0.6923 | 0.68 | 2000 | 0.7892 | 15.3553 | 41.9548 | 16.3636 | 38.1268 | 38.1269 | 42.7082 | 24.7427 | 15.632 | 10.351 | 11.2806 |
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 21, 2023
- Updated
- Aug 21, 2023