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IC_ver6d_coco_swin_gpt2_50Bpc_1e
VK246/IC_ver6d_coco_swin_gpt2_50Bpc_1e
IC_ver6d_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. --
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At a glance
- Task
- Image-Text-to-Text
- Library
- transformers
- Model type
- vision-encoder-decoder
- Access
- Public
- Created
- Jul 14, 2023
- Updated
- Jul 14, 2023
- SHA
- 80185a8d
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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_ver6d_coco_swin_gpt2_50Bpc_1e
This model is a fine-tuned version of VK246/IC_ver6c_coco_swin_gpt2_50Apc_1e on the coco dataset. It achieves the following results on the evaluation set:
- Loss: 0.7897
- Rouge1: 42.1846
- Rouge2: 16.6343
- Rougel: 38.2927
- Rougelsum: 38.2913
- Bleu: 10.4949
- 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 |
|---|---|---|---|---|---|---|---|---|---|
| 0.7741 | 0.17 | 500 | 0.8245 | 40.8216 | 15.539 | 37.1564 | 37.1436 | 9.6536 | 11.3063 |
| 0.7813 | 0.34 | 1000 | 0.8155 | 41.2707 | 15.9841 | 37.4357 | 37.4254 | 10.033 | 11.3063 |
| 0.782 | 0.51 | 1500 | 0.8061 | 41.6066 | 16.0222 | 37.802 | 37.8009 | 9.9619 | 11.3063 |
| 0.79 | 0.68 | 2000 | 0.7985 | 41.6881 | 16.2489 | 37.9303 | 37.9178 | 10.3074 | 11.3063 |
| 0.7888 | 0.85 | 2500 | 0.7929 | 42.1145 | 16.5388 | 38.2401 | 38.2324 | 10.3546 | 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 14, 2023
- Updated
- Jul 14, 2023