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Vit-GPT2-COCO2017Flickr-115k-nlpconnect
Image-Captioning-ML/Vit-GPT2-COCO2017Flickr-115k-nlpconnect
Vit-GPT2-COCO2017Flickr-115k-nlpconnect is a image-text-to-text model from Image-Captioning-ML. 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. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Image-Text-to-Text
- Library
- transformers
- License
- apache-2.0
- Model type
- vision-encoder-decoder
- Access
- Public
- Created
- Jul 15, 2024
- Updated
- Jul 18, 2024
- SHA
- 7f0fd564
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Base models
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. -->
Vit-GPT2-COCO2017Flickr-115k-nlpconnect
This model is a fine-tuned version of NourFakih/Vit-GPT2-COCO2017Flickr-115k-nlpconnect on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.4978
- Rouge1: 40.7656
- Rouge2: 15.3367
- Rougel: 36.9775
- Rougelsum: 36.9808
- Gen Len: 11.8545
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: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0
Training results
| Training Loss | Epoch | Step | Gen Len | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|---|---|---|---|---|---|---|---|---|
| 0.4218 | 0.2783 | 2000 | 11.7001 | 0.4402 | 40.8374 | 15.0971 | 36.9258 | 36.9122 |
| 0.4071 | 0.5565 | 4000 | 11.2742 | 0.4353 | 41.1785 | 15.7543 | 37.5183 | 37.5112 |
| 0.3914 | 0.8348 | 6000 | 11.7367 | 0.4345 | 41.4425 | 15.991 | 37.5387 | 37.5422 |
| 0.3367 | 1.1130 | 8000 | 11.8434 | 0.4481 | 41.0677 | 15.8609 | 37.3991 | 37.3749 |
| 0.3265 | 1.3913 | 10000 | 11.6695 | 0.4518 | 41.3243 | 16.1077 | 37.5478 | 37.5367 |
| 0.3158 | 1.6696 | 12000 | 11.7170 | 0.4556 | 41.3022 | 15.9154 | 37.3943 | 37.3924 |
| 0.3094 | 1.9479 | 14000 | 11.5969 | 0.4602 | 41.411 | 16.1338 | 37.6313 | 37.6262 |
| 0.2639 | 2.2262 | 16000 | 11.8349 | 0.4871 | 40.8402 | 15.4182 | 36.9302 | 36.9355 |
| 0.2515 | 2.5045 | 18000 | 0.4940 | 41.0116 | 15.4407 | 37.0026 | 37.0188 | 11.8727 |
| 0.253 | 2.7827 | 20000 | 0.4978 | 40.7656 | 15.3367 | 36.9775 | 36.9808 | 11.8545 |
Framework versions
- Transformers 4.42.3
- Pytorch 2.1.2
- Datasets 2.20.0
- Tokenizers 0.19.1
- Task
- Image-Text-to-Text
- Library
- transformers
- Type
- vision-encoder-decoder
- License
- apache-2.0
- Created
- Jul 15, 2024
- Updated
- Jul 18, 2024